Geography and Environmental Planning
Year:2016 | Volume:27 | Issue:3 (63) |Papers Count:11

Considering the importance of snowfall in supplying water of different regions especially mountainous areas, accurate estimation of snow water equivalence and changes of its coverage would be effective in agriculture, energy, management of reservoir and flood warnings. In this study, in order to estimate the runoff from melting snow in Shahrchay basin, snow cover for water year of 2012-2013 were extracted in ENVI software by using images of Modis satellite with a 1 km spatial resolution. Then, by using the Hec_GeoHMS accession in the GIS software, meteorological characteristics of the basin were obtained. In the next step, the snow-melt runoff was simulated by importing snow cover data, meteorological variables and indicators for the SRM model. The results showed that the river flow share of snow melting is impressive in March and April, but with the increase in the degree of air temperature in June, the proportion of rain is more impressive. Also, simulation results indicate high accuracy of this model, so that the coefficient of determination and volume percent of error of model was 0.9 and %1.96, respectively.

Rivers through production, movement and storage of sediments are one of the most important factors that are modifying the earth’s surface. Historically, some rivers selected as the boundary lines between the countries and have acquired additional importance. Rivers channel, particularly alluvial bed rivers are continuously changing and this can cause many problems. In this study, lateral movement of the Aras River, 15 km away from west of Aslanduz city to exit of the river in Iran’s border, are investigated in two time periods, 2000 and 2014. This river has a great importance in relation to water supply in the northwestern parts of the country. Moreover, in the large distances, forms Iran boundary line with the countries of Armenia and Azerbaijan. Therefore, research on the lateral changes of river becomes necessary. Topographic maps with scale of 1: 50, 000, digital elevation model (DEM) with 27 m resolution, and satellite imagery (Landsat 7 ETM+satellite sensor& Landsat 8 OLI satellite sensor) are most important materials in this research. Studied channel reach of Aras River for two time periods, 2000 and 2014 were extracted by processing satellite images. Then, channel based on morphology and changes trend was divided into 21 transects, and quantitative indicators were calculated for each transect. To analyze the river plan form, were used central angle and sinuosity coefficient. Finally, the average of channel migration rate was calculated during the past 14 years. Comparison of the central angle and sinuosity coefficient values of the river channel within each transect for the periods 2000 and 2014 represents an increasing trend for most of the transects, which indicates river meanders are active. In fact, large quantities and unusual migration rate in some transects related to the avulsion. Most likely, the avulsion caused by the river flooding, especially in the spring and disturbances due to the confluences. In some cases, combined these factors associated with interventions variables such as effects of confluences has caused the channel movement is very significant, and the unusual. Finally, it can be said that although channels have been changed continuously by lateral migration, cutoffs, and avulsion, But in 2014 compared to 2000, little change has occurred in the channel platform, and decrease or increase the number of bends, central angle and sinuosity coefficient are the result of natural function of meandering rivers. Therefore, the study river is close to dynamic equilibrium.

In this paper daily MODIS Terra and MODIS Aqua data were applied to calculate seasonal clustering of snow-covered days in Iran. These data are available in 500 * 500 meters. The applied data in this study are the finest available data for MODIS products. As the first step, numerical snow data were collected in Matlab software and then some algorithms were exploited to reduce cloud cover. After preparation of data the mean matrix of solar months from Farvardin to Esfand was prepared in Matlab. The dimension of the Matrix was 12 * 7541502 that rows represent each month and the columns depict spatial pixels. In the second step, the Euclidean distance was then calculated using ward method in Matlab. The findings of this study indicated that there are four snow-covered seasons in Iran. No snow season includes the months of Ordibehesht to Khordad, the transient months that are Farvardin and Aban, the shell of snow-covered season includes the months of Azar and Esfand. And the core of snow-covered season that incorporates the months of Dey and Bahman. And we also calculated for each of the climate season and each of solar months the number of snow-covered days and their areas in Iran. Investigations revealed that the highest area of one day snow-covered day is in the month of Dey. In this month the extent of one day snow-covered days covers 15 percent of the country. In the last step, the relation between snow-covered days and altitude was explored using Iran’s Digital Elevation Model. The results confirmed that in each of season this relation is different.

Since locating temporary housing at the time of earthquake disaster is done regardless of standard criteria by relief organizations, it may pose many complications, especially in large cities. To avoid such problems, a written action plan is needed for zoning seismic prone areas in settlements such as Ahvaz city, in terms of hazardous areas, safe areas for temporary housing after the disaster, and identifying the optimal routing to reach safe areas. In this study, the above-mentioned objectives have been studied using Fuzzy inference, Fuzzy hierarchical analysis and GIS in district “one” of Ahvaz metropolitan city. For this purpose, the most important data has been collected and used to locate high-risk as well as secure areas and also identifying the optimal routs to reach safe areas. Based on the results, Fuzzy Inference System shows 85% whereas, the Fuzzy hierarchical analysis exhibits 41% agreement with expert’s choice. This results showed the higher capability of fuzzy inference system as compared to hierarchical analysis. To identify safe locations for temporary housing post to earthquake disaster, after reviewing the type and land-use of the proposed areas using two models, in Fuzzy Inference System Model, 25 sites and in the Fuzzy hierarchical analysis, 18 sites of temporary housing were determined. In terms of optimal routing, the results showed that, both Genetic and Dijkstra algorithm are appropriate and applicable.

Rainfall is the most variable climatic elements. The changes occur in the location and the time dimension in the form of regional climate. The purpose of this study was to investigate the spatial autocorrelation of Iran's heavy and super heavy changes. For this purpose, the daily rainfall data of 664 meteorological stations during the period 1950-2010 have been used. In order to analyze changes in rainfall within a decade, geostatistical techniques such as spatial autocorrelation analysis of hot spots, statistics Getis-Ord Gi along with programming in Matlab environment and the Surfer and the GIs were used. The results of this study indicated that the Caspian coast, North West and West along the western foothills of the Zagros Mountains of Iran, the inner regions of Iran and southern parts of South East and North East of Iran had the highest precipitation of heavy and super heavy requirements. Spatial pattern of heavy precipitation showed that the maximum positive spatial autocorrelation pattern of heavy precipitation, despite their different periods of oscillation, but includes areas of West, North West and West coast of the Caspian Sea. While this is a negative spatial autocorrelation pattern of heavy precipitation, it is observed frequently in central Iran and parts of the East, particularly in Zabul. Patterns of heavy precipitation are similar to heavy precipitation.

Atmospheric emissions from industrial establishments are one of the major sources of environmental pollution. One type of industry that causes particle pollution is the cement industry that Heavy metals are among the most relevant substances emitted during the process of cement manufacture. The aim of the study is to determine the major source and extent of metal pollution in soils vicinity of the cement factory in Behbahan city. Therefore, sixty one soil samples were collected from around the cement factories in Bebahan area. The samples were obtained at the depth 5-10 cm and were analyzed for Al, Pb, Cd and Ni by Inductively Coupled Plasma (ICP). In the samples of the studied soil, the average of the recorded concentration of elements for Al, Pb, Cd and Ni are 83.26, 64.69, 75.29 and 64 (ppm), respectively. The order of the average frequency of the heavy metals concentration is of Al>Cd>Pb>Ni. The results further revealed that the metal distribution were in a fluctuating manner considering various distances and directions from the cement facility, as it was observed that the mean metal concentrations of the soil decrease as distance from the cement facility increased for most metals. In this study, three contamination indexes have been used to express the distribution of soil pollution in the area. The result of the present study showed that all the metals were deficiency to minimal enriched in all distances, since the EF values of the metals are smaller than 1.5. Geoaccumulation index of the soil sampling can explain that the Cd element is lying with extremely contaminated area and the Pb element is lying with low contaminated area. The PLI was calculated for the overall distances and showed uncontaminated area than heavy metals in background value.

The outbreak of environmental problems and its increasing trend is the subject of study in the environmental literacy framework for many experts. The role and impact of rural farmers on reducing the environmental problems is significant. Farmers possess and cultivate large areas of national land, so they may cause irreparable damage to the quality of earth and environment, if they lack environmental literacy such as knowledge, attitude, and behavior. Based on this, the aim of the present research is to study the environmental literacy level of farmers in the above mentioned dimensions. Therefore, problems involving these issues will be solved by teaching rural farmers. Methodology of the present study is descriptive-analytical done through data collection, along with library and field studies. Statistical population of the research includes all families in villages of rural district of Zoeram located in Shirvan, of whom just 139 heads of families were chosen as the sample by Cochran formula. A questionnaire was the main tool of the research. Validity and reliability of the test was calculated respectively through Specialized Panel and Cronbach Alpha. Using a T-test, the findings of the research revealed that the level of knowledge and environmental awareness in rural farmers is average and environmental behavior is lower than average. In addition, the correlation coefficient showed that there is a direct and significant relationship between dimensions of environmental literacy (knowledge, attitude, and behavior). Finally, applying the Vikor’s model, we got the result that above mentioned farmers possess different and unequal levels of knowledge, attitudes, and behavior regarding environmental literacy.

Pistachio is an aridity plant in bio-climatic zones of Irano-Turanian. Low rainfall and long dry season usually separated this area from other parts of regions. The purpose of this research is to evaluate different types of Pistachio (Acer cineracens- Pistachio, Amygdalus- Pistachio, Pistachio atlantica and Ziziphus- Pistachio) using multivariate statistical methods in Mond basin. Twenty six monthly climatic variables based on their ecological importance were selected from 18 synoptic stations within and out of basin and were distinguished by using Principal component analysis method, so that the 26 original variables were reduced into 3 components. Temperature, rain, and radiation-wind component were allocated, 56.3, 26.5 and 6.4 percent and totally 89.2 percent from total variance. Then forest type map of Pistachio were exactly graded as interpolation of climatic values and component score and based on this, the key climatic elements effective to Pistachio distribution were analyzed. The results showed that habitat of Pistachio types were moderate, semi hot and semi-arid, hot and semi dry and hot, dry. The elevation range of vegetation types in the basin was 900-2600 meters above sea level. Due to the specific conditions prevailing in the basin (low altitude and high humidity), various types of Pistachio have not been seen in hot and humid temperatures region.