Geography and Environmental Sustainability
Year:2020 | Volume:10 | Issue:34|Papers Count:8

The natural contrast between alluvial and aeolian geomorphic systems on the western margin of the Petergan Playa creates a balanced and stable environmental condition, while human intervention in the one of these systems leads to environmental instability and natural hazard expansion. In this paper, having determined the territory of the alluvial and aeolian landforms, morphology and origin of aeolian shapes have been carried out by stepwise method and the geomorphology of alluvial shapes has been studied and classified using satellite images, aerial photographs and field surveys. The morphotectonic response of alluvial systems in contrast to the aeolian systems has been calculated using neotectonic indices. Finally, using the indices of motion, velocity, contact angle, and variations of the alluvial and aeolian landforms extracted at two different time points from the satellite images, the types of contrast and possible contact between them are determined and analyzed. According to the results, in 10 years about 11. 3% of the territory of alluvial landforms has been converted to aeolian ones. Thus, aeolian systems overwhelm the region's alluvial systems. The predominance of aeolian systems has been made by diverting and blocking the flow of water and flowing over the channel shores caused by the movement of sand dunes and in many cases ponds and other channels have been created along the main channel of the river. The permanent alluvial systems in the area show stable and cyclical behavior so that the dominance of alluvial systems decreases to a certain extent during the activity seasons of the aeolian systems. The research findings show that during the 10-year period, only 1. 8% of the territory of the aeolian landforms in the region has been converted to alluvial landforms. This type of contrast can be observed along the permanent river of Tajnood which passes through the sand dunes on the eastern slope of Mount Khaje.

Lightning is one of the most severe weather hazards that will cause significant economic, social and environmental damage each year. The prediction of a lightning is a very difficult task due to the spatial and temporal expansion of weather either physically or dynamically. Therefore, timely forecasting of lightning and evaluation of the best data mining model is effective in reducing damage. In this research, the data of the years 2012_2018 of the Meteorological Station of Rasht were used, including dependent variable of occurrence and non-occurrence of lightning during 7 years and independent variables of factors affecting lightning including temperature, relative humidity, cloudy, wind speed, wind direction, pressure air and Previous day's lightning. After preprocessing and processing data, data mining models including Classification & Regression Tree (CART), Chi-squared Automatic Interaction Detector (CHAID), Induction of Decision Trees (C5) and neural networks Radial Basis Function (RBF), Multi Layer Perceptron (MLP) and Support Vector Machine (SVM) were used in SPSS Modeler Ver 20 software. The results of the models were compared with the Comparative Criteria and the Receiver operating characteristic (ROC) curve. According to the results of the models, the probability of lightning occurrence is higher in the months of May, June and July than in other months and the rate of occurrence from spring to winter has a decreasing trend, while in winter it is at least. CHAID tree with a specificity rate of 0. 794 and a minimum false positive rate of 0. 205 and the SVM model with a correct prediction of 0. 773 and an error rate of 0. 475 and precision of 0. 855 have optimum performance compared with other models.

Soil salinity and soil salinization as one of the problems facing agriculture and natural resources are of great importance which needs to be prevented with proper knowledge. In this regard, it is important to obtain information about soil salinity and vegetation, such as their amount and distribution. The use of satellite data enables extensive study of soil salinity and vegetation. Since vegetation in most arid and semi-arid regions is strongly influenced by soil properties such as salinity, therefore, this study investigated the effects of Interceptor Drain on soil salinity and vegetation changes using remote sensing capabilities in a 15-year interval. Results showed that construction Interceptor Drain in Salt Marsh Qazvin plain had no effect on soil salinity changes and vegetation cover. According to the results of correlation test between measured soil elements and satellite image bands, bands 5 and 7 were highly correlated with soil SAR (Sodium Adsorption Ratio) index prior to drainage construction and thus, the two bands after drainage construction had a significant correlation with soil EC (Electrical Conductivity) index. In fact, indices including red and infrared bands showed a significant relationship with soil salinity parameters. Also the results of correlation test of remote sensing indices and ground data in the salinity area showed that SI (Salinity Index) index had a highly significant correlation with soil salinity data.

Conservation planning needs to identify the perceptions of local communities about the distribution of uses. Required areas for supporting welfare of these communities within and around protected areas is called community use zone. Based on theoretical foundations and given that every place has value or values for local communities, it is possible to identify local values by combining participatory approach and explicit spatial approach. The aim of this study is to identify community use zone in Dena district and in the vicinity of the Dena protected area. In this regard, ethnography is applied by practices such as semi-open questionnaire, field observation and literature review and then is complemented by participatory mapping. Collecting data of local values (Subsistence, economic, cultural and conservative) is continued until the information saturation. Participants marked these hotspots of providing services on four basic maps. After digitizing the data, the spatial overlapping of these areas has been investigated. Community use zone is designated by counting the overlaps of subsistence, economic, and cultural values. Most of this zone is around rivers, roads and settlements. Within the Dena preserved area is influenced by economic and cultural uses. The conservative value identified outside the protected area requires participatory conservation planning, too. Dual-value and three-valued area in the community use zone should be a priority in educational planning and financial supporting for sustainable use. Future programs in Dena district should be focused on such actions: Prevention from firing and cultivating in the forests, prevention from land use change, increasing irrigation efficiency, proper cultivation management, prevention from irregular harvesting medicinal and edible plants, and prevention from illegal hunting of wildlife. Applying the method of this research provides a common language for the dialogue between conservation and community uses. It also provides the ground of training, empowering and attracting the participation of local communities and learning from them.

The Urban Heat Island (UHI) describes the temperature difference between urban and rural temperatures. Finding urban heat island mitigation strategies is of great importance, given expected influences on human health and air quality. This study presents numerical simulations over a summer period to investigate the impact of urban heat island control measures on Tehran urban air quality. The WRF-Chem Chemical Mesoscale Model is used to investigate the effect of increasing urban vegetation and highly reflective surfaces on the concentration of primary pollutants (CO, NO) as well as secondary pollutants (O3) in urban canyons. In order to account for the heterogeneity of urban areas, a multi-layered urban canopy model is coupled with WRF-Chem. Using this canopy model at its broad range requires introducing several urban user classes in WRFChem. Tehran metropolis is considered to simulate designed experiments in the summer of 2016. The selected reduction measures in the simulations are able to reduce the urban temperature by about 1-3 degrees Celsius and average daily ozone concentration by 5 to 10 percent. The modeling results also presented secondary negative effects on urban air quality, which is strongly related to the reduction of vertical mixing in the urban boundary layer. The simulation results show a 1 to 20% increase in the primary pollutants (NO and CO). Despite the daily average decrease in ozone concentration, highly reflective surfaces due to severe short-wavelength radiation that accelerates photochemical reactions can lead to an increase in the peak ozone concentration by up to 9% at noon hours.

The forests of the Zagros are one of the most important and fundamental treasures of the country, which plays a key role in providing water and soil resources in this region. The geographical distribution of different plant communities is dramatically dependent on climatic conditions. Changes in climatic elements, such as precipitation, can cause long-term and short-term reactions of various plant colonie. The main purpose of this study is to reveal the spatial changeability of Lorestan forest NDVI index in response to rainfall changes. The vegetation index of Lorestan was detected using Landsat 8 and 5 imageries during 2000-2017. The monthly and annual rainfall also has been obtained using accumulated monthly rainfall of 9 synoptic stations of Lorestan province. The Pearson correlation matrix has been used to analyze the relationship between annual variation of forest cover area and qnnual rainfall index. The results showed that the EVI> 0. 4 threshold can be considered as the threshold of the province's forest cover. The correlation analysis showed that the 18-year time series of forest cover, was correlated with the spatial distribution of annual rainfall in Lorestan Province by 0. 72 that is significant in 0. 95 confidence level (P_value=0. 05). Spatial analysis of the implementation of the greenness estimator model showed that the rainfall threshold of oak greenery (EVI> 0. 4) was equal to 320 mm, above which the EVI index increased by 0. 88 for each millimeter of rainfall growth of the studied oaks.

Land subsidence, as one of the natural and geological hazards, can be caused by human activities such as long-term discharge of groundwater and traditional irrigation farming. In the last two decades, climate change and successive droughts, unsustainable management of water resources and overexploitation of groundwater as well as population growth have caused land subsidence in Shahriar plain in the west of Tehran province. The present study aims to monitor and estimate land subsidence using Interferometric Synthetic Aperture Radar (InSAR) approach. Moreover, it tries to investigate the relationship between groundwater level and subsidence rate. Therefore, the time series of the ENVISAT-ASAR satellite images from 2003 to 2010 were used. The Small BAseline Subset (SBAS) algorithm was applied to analyze the time series of land surface displacement and to generate the mean displacement velocity map. The findings from time series analysis of InSAR data indicate a continuous subsidence occurrence in the agricultural lands of the region. The mean velocity of deformation along the satellite line of sight (LOS) in the time period of study, shows the displacement at an average rate of-10 cm / year and a maximum rate of-27 cm / year in the Shahriar plain in the west of Tehran province. Over this time period, groundwater level decreases about 0. 5 to 1. 5 m in the aquifer storage at 12 observational wells located in the study area. The overall correlation between changes in groundwater level and subsidence rate was estimated circa 89. 45 percent, which indicates a strong relationship between subsidence and groundwater exploitation in the region.