Predicting of dust storm source by combining remote sensing, statistic-based predictive models and game theory in the Sistan watershed, southwestern Asia

Dust storms in arid and desert areas affect radiation budget,air quality,visibility,enzymatic activities,agricultural products and human health.Due to increased drought and land use changes in recent years,the frequency of dust storms occurrence in Iran has been increased.This study aims to identify dust source areas in the Sistan watershed(Iran-Afghanistan borders)-an important regional source for dust storms in southwestern Asia,using remote sensing(RS)and bivariate statistical models.Furthermore,this study determines the relative importance of factors controlling dust emissions using frequency ratio(FR)and weights of evidence(WOE)models and interpretability of predictive models using game theory.For this purpose,we identified 211 dust sources in the study area and generated a dust source distribution map-inventory map-by dust source potential index based on RS data.In addition,spatial maps of topographic factors affecting dust source areas including soil,lithology,slope,Normalized difference vegetation index(NDVI),geomorphology and land use were prepared.The performance of two models(WOE and FR)was evaluated using the area under curve(AUC)of the receiver operating characteristic curve.The results showed that soil,geomorphology and slope exhibited the greatest influence in the dust source areas.The 55.3%(according to FR)and 62.6%(according to WOE)of the total area were classified as high and very high potential dust sources,while both models displayed acceptable accuracy with subsurface levels of 0.704 for FR and 0.751 for WOE,although they predict different fractions of dust potential classes.Based on Shapley additive explanations(SHAP),three factors,i.e.,soil,slope and NDVI have the highest impact on the model's output.Overall,combination of statistic-based predictive models(or data mining models),RS and game theory techniques can provide accurate maps of dust source areas in arid and semi-arid regions,which can be helpful for mitigation of negative effects of dust storms.

Climatic variations of general atmospheric circulation,precipitation and river flow of the territory of Kazakhstan

Methods of calculating the basic hydrological characteristics of a water resource assessment, as well as the planning and manage- ment of their long-term use are based upon the concept of stationarity of long-term flow fluctuations. However, data of researches by hydrologists and climatologists clearly indicate that there are long-period changes in the characteristics of precipitation and riv- er flow. This article discusses the variations of annual precipitation and fiver flow in the Ishim River Basin in Kazakhstan, based on the W, C and E classification developed by GY. Vangengeim who analyzed the long-term variability of anomalies by the num- ber of days with some form of atmospheric circulation. From this study, the largest anomaly of the macro-circulation processes was revealed, and a comparative analysis of the number of days with various forms of atmospheric circulation and precipitation anomalies was made. It was demonstrated that the nature of atmospheric circulation depends on the distribution of precipitation; however, precipitation is also highly dependent on local physiographic conditions. The analysis of anomalous precipitation during the maximum number of days of positive anomalies with various forms of atmospheric circulation was also carried out. This study presents some results t^om the preliminary analysis of annual river flow linked with forms of atmospheric circulation.

Assessment of the Effect of Neyshabur Green Spatial Configuration on the Temperature of Land Surface and Heat Islands

Urban heat island is a global issue and a consequence of rapid urbanization that leads to higher land surface temperature in urban areas. The range is 0.6°C - 1.3°C compared to rural and suburban areas. LST (Land surface temperature) is an important parameter in determining the heat island. Understanding the relationship between green space configuration and LST is essential to the effective design of the mechanisms, which reduce the effect of urbanization on UHI (urban heat island). This study examines the correlation between LST and spatial configuration of green space in the urban landscape of Neyshabur city, Iran. Satellite images are obtained from Landsat ETM+ satellite sensor with a spatial resolution of 60 meters in August 2010 and used for the estimation of LST. In order to identify the configuration of green space, five configuration metrics LSI (landscape Shape Index), MPFD (Mean Patch Fractal Dimension), ED (Edge Density), MPS (Mean Patch Size) and MSI (Mean Shape Index) are used. In addition, configuration of the green space and temperature is compared by Pearson’s correlation-coefficient. Negative values represent a suppressive/negative effect on each other;the fact that other indicators of spatial configuration are inversely related to temperature means that they weaken the effect of UHI. Results of the study showed that the spatial configuration of the green space notably affects increased LST and UHI. On the other hand, the configuration indicator with the greatest impact on LST was ED, because with increase in margin density further decreases LST.

An Assessment of Temporal and Spatial Distribution of Thunder Storms in Iran

The main purpose of this study is to investigate temporal and spatial distribution of thunderstorm frequency in Iran. In order to do study, observed statistical data of the present weather codes of thunderstorm (17, 29, 91 - 99) in 50 synoptic stations around the country were used in a 35 years statistic period (1979-2013). The results of the study showed that the phenomenon occurs mostly in southwest, west and northwest regions of Iran. Thunderstorm occurrence reduces when moving toward east. Maku station in northwest of Iran shows the maximum thunderstorm frequency during the statistical period (mean annual of 31). Jask station in southern Iran (mean annual of 2) has shown minimum thunderstorm occurrence during the statistical period. In the eastern regions of Iran, Torbat Heydarieh station revealed higher frequency than the other stations which was because of high mountains like Qaenat. In terms of temporal distribution, spring showed the highest frequency of the phenomenon. In monthly scale, the maximum frequency of hail downfall happens in April and May. In hourly scale, the maximum occurrence of thunderstorm observed at 12 - 18 p.m. for UTC time.

“Water-Colouring” and Geomorphologic Features of the Marl Hills in Changing Quality of Soil and Water

Water scarcity has always been one of the most important obstacles in the process of agricultural development in arid and low-rainfall climates. In farming, the water quality also plays an important role;as the poor quality of water can be one of the limiting factors in this sector that in addition to the agricultural problems has also caused soil problems. In this paper, we introduce and study an indigenous method of water conservation and soil protection in the east of Iran termed as “water-colouring” and the role of geomorphologic features of marl hills in one of the rivers located in the southern slopes of the Joghtay Mountain (Kalateh-Sadat Watershed). In this study, field observation, sampling and analysis of water and sediment, physicochemical experiments, SPSS software for statistical analysis and satellite images have been used to produce digital models. Finally, the effects of muddy water and clear water have been compared in terms of chemical quality and productivity of agricultural land. The results show that the method of water-colouring is the best indigenous-economical method for moisture retention and regeneration of the agricultural land soil. Given the statistical reasons and studying the other researches in this field, water-colouring causes change texture and soil composition, fertility of agricultural land and reduce the losses due to evaporation and infiltration.

Responses of Annual Variability of Vegetation NPP to Climate Variables Using Satellite Techniques in Gadarif State, Sudan

Plants play an essential role in matter and energy transformations and are key messengers in the carbon and energy cycle. Net primary productivity (NPP) reflects the capability of plants to transform solar energy into photosynthesis. It is very sensible for factors affecting on vegetation variability such as climate, soils, plant characteristics and human activities. So, it can be used as an indicator of actual and potential trend of vegetation. In this study we used the actual NPP which was derived from MODIS to assess the response of NPP to climate variables in Gadarif State, from 2000 to 2010. The correlations between NPP and climate variables (temperature and precipitation) are calculated using Pearson’s Correlation Coefficient and ordinary least squares regression. The main results show the following 1) the correlation Coefficient between NPP and mean annual temperature is Somewhat negative for Feshaga, Rahd, Gadarif and Galabat areas and weakly negative in Faw area;2) the correlation Coefficient between NPP and annual total precipitation is weakly negative in Faw, Rahd and Galabat areas and somewhat negative in Galabat and Rahd areas. This study demonstrated that the correlation analysis between NPP and climate variables (precipitation and temperature) gives reliably result of NPP responses to climate variables that is clearly in a very large scale of study area.

Modeling groundwater nitrate concentrations using spatial and non-spatial regression models in a semi-arid environment

Nitrate nitrogen(NO_(3)^(-)N)from agricultural activities and in industrial wastewater has become the main source of groundwater pollution,which has raised widespread concerns,particularly in arid and semi-arid river basins with little water that meets relevant standards.This study aimed to investigate the performance of spatial and non-spatial regression models in modeling nitrate pollution in a semi-intensive farming region of Iran.To perform the modeling of the groundwater's NO_(3)^(-)N concentration,both natural and anthropogenic factors affecting groundwater NO_(3)^(-)N were selected.The results of Moran's I test showed that groundwater nitrate concentration had a significant spatial dependence on the density of wells,distance from streams,total annual precipitation,and distance from roads in the study area.This study provided a way to estimate nitrate pollution using both natural and anthropogenic factors in arid and semi-arid areas where only a few factors are available.Spatial regression methods with spatial correlation structures are effective tools to support spatial decision-making in water pollution control.

哈萨克斯坦巴尔喀什湖沉积物粒度特征及其对区域环境变化的响应

湖泊沉积物中的粒度参数记载了丰富的流域环境变化信息,可为无器测资料地区重建古环境变化序列提供可靠的途径。通过对巴尔喀什湖岩芯沉积物中粒度、磁化率等环境代用指标的分析,结合放射性137Cs定年以及流域气候、湖泊水位等器测记录数据,研究了巴尔喀什湖沉积物中粒度变化特征及其环境指示意义。结果表明:巴尔喀什湖沉积物中黏土质(<4μm)组分平均含量为20.32%,细粉砂质(4~16μm)为40.13%,中粉砂质(16~32μm)为22.86%,粗粉砂质(32~64μm)为10.55%,砂质(>64μm)为6.13%。通过粒径标准-偏差法提取了沉积物中环境细颗粒敏感组分(F1,6.61~10.00μm)和粗颗粒敏感组分(F2,45.71~69.18μm)。研究表明在人类活动影响不断加强的背景下,粒度敏感组分的含量变化不能敏感的反映湖泊水位、入湖径流乃至区域气候的变化,而与沉积物中磁化率所反映的人类活动强度变化存在较为显著的相关关系(r=0.870,P<0.01),这可能与人类活动增强导致的流域内富含磁性物质的细颗粒碎屑物质被搬运入湖有关,湖泊沉积物中磁化率升高的同时,湖泊沉积物中细颗粒物质增加。研究结果可为长时间尺度下古环境重建研究提供重要参考依据,同时也对揭示流域人类活动对湖泊环境的影响具有一定的科学意义。

Fluctuating temperature modifies heat-mortality association around the globe

Studies have investigated the effects of heat and temperature variability(TV)on mortality.However,few assessed whether TV modifies the heat-mortality association.Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries.TV was calculated as the standard deviation of the average of the same and previous days’minimum and maximum temperatures.