Mahmood Damizadeh; Rasool Mahdavi; Ali Akbar Noroozi; Hamid Gholami; Arshk Hollisaz
Abstract
Dust storms are one of the atmospheric phenomena which has many negative effects for Hormozgan Province, as one of the most important population and tourism centers in the south and with significant and strategic facilities in the country. For this reason, todays determining the hotspots and areas affected ...
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Dust storms are one of the atmospheric phenomena which has many negative effects for Hormozgan Province, as one of the most important population and tourism centers in the south and with significant and strategic facilities in the country. For this reason, todays determining the hotspots and areas affected by the storm, as well as identifying important routes of entry and movement is one of the most important needs of relevant organizations in this province. In order to study the dust phenomenon in Hormozgan Province, first, all meteorological data of 12 synoptic stations in the region between 2000 and 2018 were analyzed and 48 dust storm events were identified that their horizontal visibility has decreased to less than 1000 meters and dust mass detection operations were performed using MODIS satellite images and four detection algorithms of Ackerman, TDI, TIIDI and NDDI and areas affected by storm as well as areas of origin were identified. HYSPLIT particle Lagrangian diffusion model was used to route the motion of the dust storm and the entry routes of dust storms into the province also, its routes and areas that have the most impact in this area were identified. Comparing results of four dust detection algorithms indicated better performance of TDI algorithm compared to other algorithms in detecting the focus and mass of dust in the area. According to the results, eastern regions of Hormozgan Province, Jazmourian Wetland, eastern Sistan and Baluchestan, western regions of Afghanistan and Pakistan, as well as central and southern regions of Saudi are one of the most important centers of dust production in the region. Investigating HYSPLIT model maps indicates the existence of three general routes of entry and creation of dust storms in the area which includes the southwestern regions of the country, the south-north route and the north and northwest route. Also, based on model results, about 53.7% of the path of movement and the release of dust after a storm is to the north and northeast direction which causes the spread of pollution and intensification of dust concentration in cities such as Bandar Abbas, Qeshm, Minab, Rudan, Jiroft, Kahnooj, Bam, Iranshahr, Khash, Mirjaveh and Zahedan. Also, about 22.3% of the storms in the region consider the southern route, 14.8% the south-west route and 9.2% the east route to continue their navigation.
Mahmood Damizadeh; Rasool Mahdavi; Ali Akbar Noroozi; Arshk Hollisaz; Hamid Gholami
Abstract
Geographical location and proximity to countries such as Saudi Arabia, Pakistan and Afghanistan as well as desert conditions and poor vegetation cover, weather instability and high winds have caused dust storms in different parts of Hormozgan province. This phenomenon is nowadays recognized as one of ...
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Geographical location and proximity to countries such as Saudi Arabia, Pakistan and Afghanistan as well as desert conditions and poor vegetation cover, weather instability and high winds have caused dust storms in different parts of Hormozgan province. This phenomenon is nowadays recognized as one of the environmental challenges in southern Iran. In order to study the dust phenomena in Hormozgan province, were first analyzed the dust data of twelve synoptic stations in the region between 2000 and 2018 Ackerman’s model, Normalized Difference Dust Index (NDDI), Thermal-infrared Dust Index (TDI) and Thermal Infrared Integrated Dust Index (TIIDI) were four Algorithm methods for dust source and plume identification using MODIS data MODIS Level 1B and MODIS Level 2 aerosol data to delineate and compares. Results showed that Qeshm station with 2762 days had the most and Minab station with 356 days had the least frequency of dust occurrence in the province. Also, 2007, 2008 and 2003 have the highest occurrence among the studied years. According to the survey data from 35716 days associated with dust phenomenon, 84% of dust events in the stations were locally originated (code 07) and 16% were of external source (06). The results also showed that the most occurrence of dust occurred in May, April and July, and the least occurrence of dust occurred in November, December and October. The results are shows all of the techniques except NDDI were successful in detecting dust plumes, but the most effective algorithm for plumes identification varied from event to event. In addition, TDI is the best algorithm comparing 3 evidence and eastern regions of Hormozgan, Jazmoorian area, Sistan and Baluchestan, and the western part of Afghanistan and Pakistan and south of Saudi Arabia are most important for dust source in Hormozgan Province.
Abstract
Homogeneous sub watershed Are useful for comparison and better understanding of the complex structure of watershed and thereby facilitating the development and management approaches specific to each class to deal with the destructive phenomena such as soil erosion, drought and flood. In this study, the ...
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Homogeneous sub watershed Are useful for comparison and better understanding of the complex structure of watershed and thereby facilitating the development and management approaches specific to each class to deal with the destructive phenomena such as soil erosion, drought and flood. In this study, the database contains 6 groups of information such as climatic and socio-economic, topography, soil, water, remote sensing were studied.These Factors converted to raster and then the pixel data converted to text data (ASCII). So matrix was produced with dimensions of 27 * 147 506. Eigenvalues and the variance associated with each factor showed that 6 first component includes a total of 83.27% of the changes. In order to select the optimal number of clusters and clustering evaluation and validation of the method, hierarchical clustering and discriminant analysis and clustering using k- mean cluster of the data was performed. Karoon Sub watersheds were classified into 16 groups.
