Journal of Spatial Analysis

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Dust particles are important atmospheric aerosol compounds. The particles are resulting performance of strong winds at the soil surface desert areas. Sources of dust are 2 types: 1- Natural Resources 2- Human Resources. Iran is located in the desert belt which this problem cause increased the frequency of dust storms, especially in South East (Sistan) and South West. China Meteorological Administration Center classifies storms based on particles type, visibility and speed storms to 4 kind: Floating Dust, Blowing Dust, Sand/Dust Storm and Sever Sand/Dust Storm. In general, the effects of dust storms in 7 of Environment (particles into remote areas, the effect of dust particles on the material, climate, oceans and deserts), public health and health (increase of respiratory diseases , cardiovascular problems, digestive, eye, skin, reduced hearing, infections, reduced life expectancy and premature death, etc.), economic (unemployment, road accidents, damage to communication lines, air, land, sea, increase water turbidity in water utilities, creating uncertainty for all economic activities, etc.), Agriculture and Livestock (negative effect on the growth of plants and animals, reduced productivity and diversification, intensification of plant and animal pests and diseases, rising costs maintenance of livestock, etc.), socio-cultural (poverty and the loss of local jobs, destruction of subcultures, rural migration to the cities, closure of educational premises, industrial units, services, etc.) and military-security (disabling weapons, food and beverage contamination, the threat of sensitive electronics and power transmission systems, and reduce the useful life sitting on warehouse equipment, logistics cargo weight gain, etc.) can be evaluated. One way to identify, evaluate and forecast dust storm modeling. Dust cycle consists of 3 parts, dust emissions, dust and subsidence transfer dust that can be simulated by models.

In this study using the WRF_Chem model with FNL^[1] input data and GOCART schema, sever dust storm in Sistan region was simulated to date 14 & 15 July 2011. Satellite images of the event was received by the MODIS sensor. Dust concentration data was received from the Department of Environment. The dust storm code, minimum visibility data and maximum wind speed data was received from the, Meteorological Organization.

The results of the simulation for dust concentration which peak amount of dust was for 21Z14July2011 and 03Z15 July 2011. Model output showed maximum wind speed 20 m/s with North to South direction in the study area. The model predicts maximum dust concentration for the latitude 31 degree North and longitude 54 degree East to 66 degree East (Within the study area). MODIS sensor images showed clearly the sever dust storm. Simulated time series in Figure 3-1 Changes in dust concentration during the event show in the Sistan region. As can be seen from the peak of the concentration of dust in 21 hours on 14 July (350 micrograms per cubic meter) and 03 hours on 15 July (425 micrograms per cubic meter) 2011 was created. Model simulation and satellite images indicated which the Sistan region, especially dry bed of Hamoun wetland in East of Iran was main source of sand and dust storm. Also, based on the model output blowing wind direction from North to South on Iran which converging these currents in East Iran caused by strong winds in the lower levels (According to the meteorological data), arise dust, increasing the dust concentration (According to Department of Environment data), increasing the dust and being transferred to the Southern regions, especially  Oman sea. To identify the source of the sand and dust storm, the path of the particle and anticipated this event cant actions and warned to stop and reduce effects its. . Simulation of dust particles in the resolution of 10 and 30 kilometers, the plains of Sistan in Iran's East region as the main source screen. The findings suggest that compliance with the maximum concentration limits on known sources of particles (especially Sistan plain dry bed of plain wetlands) is. Check drawings wear rate showed that the source of dust in the Sistan region, particularly the high potential of our wetlands dry bed of soil erosion in wind activity 120 days during the hot and dry conditions, and silt and clay up to thousands of kilometers away from their source transfers. Vector lines on maps wear rate, indicative of converging flow north-south and severe dust storms in history is this. It is better than models forecast dust events and rapid alert

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Changes in the mean and the extreme values of hydroclimatic variables are two
prominent features of the future climate. Therefore, simulating the climatic
behavior of Shandiz catchment area, an important tourist area in the northeast of
the country, will play an important role in identifying the climate condition and
potential vulnerability of these areas in the coming decades of climate change.
In this study, we will
evaluate the effects of climate change on extreme values of the basin micro scaling
precipitation and temperature in CanESM2 model using SDSM model and
simulating runoff with SWAT model in future decades.
To achieve this goal, the daily temperature and precipitation statistics of the 30
statistical years (1961-1990) of Mashhad synoptic station have been
used. The data of the CanESM2 general circulation model under RCP2.6, RCP4.5
and RCP8.5 scenarios are also used to predict precipitation, the minimum and
maximum temperature for 2041 to 2100.
According to the results, the annual precipitation rises 37 to 54 percent from 2041
to2070 compared to the observation period, and the increase in rainfall of the
2071-2100 rises 52 to 66 percent. Precipitation extreme values, the mean of
maximum and minimum temperatures in future periods in all seasons of Mashhad
station will increase compared to the observation period (1961-1990).In future decades, the average maximum temperature in Mashhad will increase from 4.6 to 0.65 degrees Celsius
and the average minimum temperature will increase 53/1 to 22/4.
By introducing micro scaled time series of the maximum temperature, temperature,
and micro scaled precipitation by SDSM model to SWAT model, the monthly time
series of Shandiz watershed runoff at Sarasiab Station was simulated for the two
periods of 2041-2070 and 2071-2100 under three distribution scenarios of RCP2.6,
RCP4.5 and RCP8.5. For this purpose, first, the model was calibrated and validated
using Shandiz hydrometric station runoff for 2003-2012, and the values of R2 were
65 and 52, respectively. Subsequently, with the introduction of micro scaled time
series of maximum and minimum temperatures, and micro scaled precipitation by
SDSM model to SWAT model, the average annual trend shows that runoff
increases in the coming decades. The lowest average annual increase for runoff is
in 2041-2070 and RCP4.5 scenario, with an increase of 56.1% over the observation
period. The highest increase of average annual monthly runoff is from 2071 to2100
under RCP 2.6 scenario with 53% to 104% runoff compared to the observation period.