Identification of sand and dust storm source areas in Iran

Sand and dust storms （SDS） are common phenomena in arid and semi-arid areas. In recent years, SDS frequencies and intensities have increased significantly in Iran. A research on SDS sources is important for understanding the mechanisms of dust generation and assessing its socio-economic and environmental impacts. In this paper, we developed a new approach to identify SDS source areas in Iran using a combination of nine related datasets, namely drought events, temperature, precipitation, location of sandy soils, SDS frequency, hu- man-induced soil degradation （HISD）, human influence index （HII）, rain use efficiency （RUE） and net primary pro- ductivity （NPP） loss. To identify SDS source areas, we firstly normalized these datasets under uniform criteria in- cluding layer reprojection using Lambert conformal conic projection, data conversion from shapefile to raster, Min-Max Normalization with data range from 0 to 1, and data interpolation by Kriging and images resampling （resolution of 1 km）. After that, a score map for the possibility of SDS sources was generated through overlaying multiple datasets under average weight allocation criterion, in which each item obtained weight equally. In the score map, the higher the score, the more possible a specific area could be regarded as SDS source area. Exceptions mostly came from large cities, like Tehran and Isfahan. As a result, final SDS source areas were mapped out, and Al-Howizeh/Al-Azim marshes and Sistan Basin were identified as main SDS source areas in Iran. The SDS source area in Al-Howizeh/Al-Azim marshes still keeps expanding. In addition, Al-Howizeh/Al-Azim marshes are now suf- fering rapid land degradation due to natural and human-induced factors and might totally vanish in the near future. Sistan Basin also demonstrates the impacts of soil degradation and wind erosion. With appropriate intensity, dura- tion, wind speed and altitude of the dust storms, sand particles uplifting from this area might have developed into extreme dust storms, especially during the summer.

Impacts of Sand and Dust Storms on Regional Economy Based on Stochastic CGE Model : A Case Study in Inner Mongolia, China

[Objectives]The paper was to study the impacts of sand and dust storms(SDS)on regional economy.[Methods]In this paper,we combined the computable general equilibrium(CGE)model and the Monte Carlo method to examine the impact of SDS on the regional economy,with a focus on GDP,price index,employment rate,industrial structure and output,income and expenditure.We extended the standard CGE model,introduced the stochastic parameters into the production module,which had significant impact on economic output,and inserted the rate of change of the total labor supply and the expenditure share of early warning and protective measures into the income and expenditure module.[Results]SDS had significant impacts on regional GDP,employment rate,and industrial output from a macro perspective,and can reduce the income of residents and enterprises and increase expenditures from a micro perspective.The impact can be reduced by taking early warning and protective measures.[Conclusions]The protective measures taken for different grades of SDS have different effects.

Discriminant Genetic Algorithm Extended (DGAE) model for seasonal sand and dust storm prediction

Here we use a Discriminant Genetic Algorithm Extended (DGAE) model to diagnose and predict seasonal sand and dust storm (SDS) activities occurring in Northeast Asia. The study employed the regular meteorological data, including surface data, upper air data, and NCEP reanalysis data, collected from 1980–2006. The regional, seasonal, and annual differences of 3-D atmospheric circulation structures and SDS activities in the context of spatial and temporal distributions were given. Genetic algorithms were introduced with the further extension of promoting SDS seasonal predication from multi-level resolution. Genetic probability was used as a substitute for posterior probability of multi-level discriminants, to show the dual characteristics of crossover inheritance and mutation and to build a non-linear adaptability function in line with extended genetic algorithms. This has unveiled the spatial distribution of the maximum adaptability, allowing the forecast field to be defined by the population with the largest probability, and made discriminant genetic extension possible. In addition, the effort has led to the establishment of a regional model for predicting seasonal SDS activities in East Asia. The model was tested to predict the spring SDS activities occurring in North China from 2007 to 2009. The experimental forecast resulted in highly discriminant intensity ratings and regional distributions of SDS activities, which are a meaningful reference for seasonal SDS predictions in the future.

Biological crust in sand and dust storm source areas of Asia and its impact on dust emission

Even though the biological crusts are critical to dust emissions,no sand and dust forecast model have considered the impacts of the biological crust in dust emission scheme.This situation mainly comes from two scientific difficulties:there is no large scale regional biological crust data available that can be used in the forecast model;there is no quantification of how biological crusts impact on sand emission.In this way,we studied the distribution of biological soil crust in sand and dust storm source areas of Central and East Asia using Moderate Resolution Imaging Spectroradiometer satellite surface reflectance data collected in 2000—2019 to determine its potential impact on dust emission according to two empirical schemes.We further evaluated the relationships between soil crust coverage,roughness length,and dust emission to study SDS source areas.We found that biological crust is widely distributed in SDS source areas of Central and East Asia,with coverage rates of 19.8%in Central Asian deserts,23.1%in the Gobi Desert,and 17.3%—32.8%in Chinese deserts(p>0.05).Cyanobacteria and lichen coverage has increased in Chinese deserts,reflecting the recent impacts of the Project of Returning Farmland to Grassland and Farmland to Forests.However,biological soil crust coverage has not increased in Central Asian deserts or the Gobi Desert,and that in Central Asian deserts continues to decrease,demonstrating the complexity of the combined effects of human activities and climate change on its distribution.Biological soil crust increased the roughness length of Central and East Asian SDS source areas by 0.14—0.62 mm.The suppression of dust emission due to biological soil crust did not change among years during the study period.The horizontal and vertical dust flux inhibition coefficient(DFIC)were 2.0—11.0 and 1.7—2.9(p>0.05),respectively,clearly showing a suppressive effect.Improvement of the ecological environment in some deserts can lead to the ability of these crusts to inhibit dust erosion errors that must be considered in the dust emission scheme for areas where crust coverage has improved.

Climate Change: Droughts and Increasing Desertification in the Middle East, with Special Reference to Iraq

Climate change impacts on Earth’s atmosphere have caused drastic changes in the environment of most regions of the world. The Middle East region ranks among the worst affected of these regions. This has taken forms of increasing atmospheric temperatures, intensive heat waves, decreased and erratic precipitation and general decline in water resources;all leading to frequent and longer droughts, desertification and giving rise to intensive and recurrent (SDS). The present conditions have led to increasing emissions of (GHG) in the earth atmosphere. All future projections especially those using (IPCC) models and emission scenarios indicate that the Middle East will undergo appreciable decrease in winter precipitation with increasing temperature until the end of this century both of which are inductive to increased dryness and desertification. Iraq as one of the countries of this region and due to its geographical location, its dependence mostly on surface water resources originating from neighboring countries, long years of neglect and bad land management put it in the most precarious and unstable position among the other countries of the region. Modelling studies have shown that Iraq is suffering now from excessive dryness and droughts, increasing loss of vegetation cover areas, increasing encroachment of sand dunes on agricultural lands, in addition to severe and frequent (SDS). These negative repercussions and their mitigations require solutions not on the local level alone but collective cooperation and work from all the countries of the region.