Journal of Spatial Analysis

Dust particles consist of important aerosols and resulting in blowing strong winds on the surface of desert areas. These particles enter the atmosphere under the influence of different factors including: weather condition (wind, precipitation and temperature), land surface (topography, humidity level, roughness and vegetation), soil features (texture, density, composition and land use (agriculture).

Today powerful dust storm destroys people lives and causes severe damages to their life and also causes financial problems in most regions of the world especially in west and southwest of Asia. Dust storm is one of the most important natural phenomena and also a kind of severe natural disaster that influence Iran and its west and southwest part. The location of Iran on the desert belt is accompanied by frequent increasing of sand and dust storm. Integral prediction of dust storm phenomena can be useful in decreasing damages caused by these storms. So synoptic-dynamic analysis of dust storms and their simulation play an important role in achieving to this goal.

In this research, we investigate severe dust storm in August 2005 that affected a large area of our country. Select of dusty days were based on minimum visibility and maximum durability of that dust storm. At first, we show the minimum of daily visibility table. These data has been provided by Meteorological Organization in 5 western cities. The synoptic maps were related to these phenomena derived from NOAA website and synoptic and dynamic interpretation has been done. We have got the data with resolution of 2.5 degree from NOAA website.

Then 700 hpa relative vorticity maps were drawn. We investigate MODIS images instrument on Aqua satellite and evaluate the amount of mass concentration of dust particles. Then the Lagrangian Integrated Trajectory Model has been used to determine the backward trajectory of dust particles. We run HYSPLIT model by GDAS data with a resolution of 0.5 degrees. At last we investigate the output of the WRE-CHEM model. This model was run to simulate dust storms in 7-10 August and FNL data with a resolution 1 degree use for initial and boundary conditions. WRF-CHEM is used to simulate dust condition and transmission. As a part of WRF model, its main application is the study of atmosphere chemistry.

At 500 hpa a very strong ridge entered Iran from the southwest. It covered all areas of our country which prevents the transference of dust to high levels of atmosphere. In 700 hpa relative vorticity maps show one day before dust storm reach to Iran a Positive voriticity is located in Iraq and Syria. So dust comes up to higher levels of the atmosphere and in dusty days in our country. There is a negative voriticity located in our country and because of downside movement of the air, dust storm happen in Iran.

Dust loading and friction velocity of outputs of the model has been drawn in dusty days. The time series of dust concentration of output models for Tabriz are compared with the concentration data of Environmental Organization of visibility data. Result show that a low pressure system is located over the Oman sea that its blaze has been extended to the northwest of Iran. On the other hand a high pressure center is located in the Europe that extended to the east of Mediterranean. So strong pressure gradient were in Iraq and Syria and they caused the creation of strong winds in their deserts which caused dust emission.

Friction velocity related to the model outputs show that the velocity of wind is high in dusty days in Iraq and Syria. So conditions are suitable for dust raining. Satellite images showed that WRF/CHEM model is simulated very well in emission, source, diffusion and the extent of the areas covered with dust. Comparing MP10 concentration of the model output with and Environment Organization data of Tabriz city show that WRF/CHEM model forecast daily changes well. But model underestimate significantly in quantity of concentration. This error may be due to a model considering only dust quantity but other pollutants affected on visibility. In general it can be said that in this event, dust concentration has been underestimated by WRF/CHEM model especially in maximum amount of PM10 concentration.

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

The correct management in natural ecosystems is not possible without knowledge of the health in its sectors. Vegetation is the most significant sector in ecosystem that has important role in its health. Resilience is one of the defining features of health vegetation The term resilience was first introduced in the study of ecological systems and demonstrates the ability of the ecosystem to maintain its performance in the face of environmental disorders. A resilience-based system is not only equipped with a disorder adjustment mechanism but also has the potential to benefit from changes in a way that lead to creating an opportunity for development, innovation, and updating. Therefore, when a change occurs, the resilience provides the needed conditions for restarting and reorganization. If this goes beyond disturbing forces, the system will have the power to return to the maximum vegetation density with the least erosion effects, otherwise the system will be vulnerable to the change that was created and could already be controlled.
This research was done in part of North east of South Khorasan province (arid climate) with the aim of quantifying vegetative resilience on behalf of ecosystem health in response to drought occurrences and long-term precipitation changes, as environmental disturbances. Therefore first, using daily precipitation data from 15 meteorological stations around the study area, their annual precipitation was extracted and was standardized by Standard Precipitation Index (SPI) over the course of thirty years (1986 - 2015). Then, the SPI index data in 15 stations were interpolated by ArcGIS software based on Inverse Distance Weighted (IDW) method and dry, wet and normal years was estimated in the study region for each year. On the other hand, from archive of satellite images of Landsat 5 and Landsat 7, an image was created for each year in study period, between 15 June and 15 July, with permanent coverage at the best of growth. Following the necessary corrections for satellite images, the average Transformed Normalized Difference Vegetation Index (TNDVI) was obtained of each image by ENVI software. Finally, effected of precipitation changes on mean TNDVI was assessed and vegetation resilience was stabilized whit selected of sever time period samples based on four effective parameters (Amplitude, Malleability, Damping and Hysteresis).

Comparison of annual precipitation variations in the thirty-year time series (1986 -2015) indicated two approximate wet and dry periods in study area. The wet period is related to the first fourteen years of the time series (1986-1999) and the dry period is related to the last sixteen years (2000-2015). In this term, severe precipitation incidents with different intensities were occurred in the study area including one case of very intense precipitation (1986), one case of intense precipitation (1991) and two cases of moderate precipitation (1996 and 1992). Also, four drought incidents were occurred including one case of intense drought (2001) and three cases of moderate drought (1987, 2006 and 2008). All precipitations (wet years) are related to the first half and most droughts are related to the second half of the studied period. In this study for fixing of vegetation resilience in study area and for calculating of its parameters, In addition to the thirty-year time series selected sever time sections. in the whole study series (1986 - 2015), maximum of mean TNDVI (49.37 %) was in 1986 (reference), the lowest mean TNDVI (43.58%) was in 2010, The year effect of the decrease precipitation and drought, and mean TNDVI in 2015 was 44.28 %. Amount of parameters amplitude, malleability and damping are respectively 5.79, 0.7 and 5.09, and hysteresis was zero (%). The result of this case showed that the vegetation has moved towards the reference state (Resilience) but has not reached to amount of reference vegetation. The most specific cases for vegetation resilience happened from 1986 to 1996 (wet period) and 2003- 2009 time sector (dry period). In the first time section amount of amplitude and malleability were 0.64 %, damping was zero and hysteresis was 0.25%. The result of this case showed that not only the vegetation was returned to the reference state but also was increased to the reference (Cross reference).So despite the reduced rainfall and occurrence of sever occurrences of drought in dry period, hysteresis parameter (0.05 %) observed in 2003- 2009 time sector too that confirmed clearly vegetation health in study area whit dry climate. 

Awareness of the health status of the vegetation and its response to long-term precipitation changes and environmental disorders, such as drought occurrence, ensure the success of the managerial plans for renewable natural resources. The present study is the second study on quantifying the vegetation resilience and the first study under dry climatic conditions in Asia (an average annual precipitation of 160 mm) conducted in Iran by calculating four factors related to resilience, and is the first study that has presented the factor hysteresis in the calculations. Despite continuous of difficult condition, the native vegetation of the study area has been able to return the reference state not only by resolving the disorder relatively, but also it has experienced hysteresis stage. A set of quantitative calculations showed despite reduced annual precipitation and drought events, vegetation has been able to maintain its resilience, which indicates the health of the vegetation in the studied ecosystem. With the presence of such amazing protective and consistent mechanisms in the vegetation of arid regions, it is possible to maintain and restore these regions by proper managerial plans.