مجله مخاطرات محیط طبیعی
پیاپی 34 (زمستان 1401)

Dust storms originate in many of the world’s drylands and may impact a wide range of negative effects on ecological, public health, and socio-economic issues. The phenomenon of dust is one of the most important environmental challenges nowadays. Therefore, Identifying the sources of dust storms is the first step to combating these devastating phenomena. Using satellite images is the most up-to-date method to identify dust sources. The present study aims to identify areas of dust generation potential in Hamadan province and the effective range. Modis and Sentinel-5 satellite imagery were used for the 2008-2019 and 2018-2020 study periods using GEE, respectively. Land-use maps, BSI, and MNDVI were considered useful indices to detect and monitor the dust generation centers. Classification of aerosol concentrations in three classes showed that the area of the first class (the highest concentration class) in Modis and Sentinel-5 images are 9875.1 and 7100.5 km2, respectively, which are Continuous polygons in Sentinel-5 and Scattered polygons in Modis images. By focusing on quantifying and overlapping land-use 2018 and actual dust centers, the results showed that most aerosols are concentrated in poor pastures and uncultivated lands in Sentinel-5 images and are concentrated in poor pastures and rainfed-agriculture in Madis images. The correlation coefficient between the two images is 81%.  Finally, Sentinel-5 satellite imagery can be used for dust detecting and monitoring. To manage these actual dust sources, reducing bare soils, increasing vegetation covers, improving water-use efficiency in agriculture, and reducing the use of groundwater in Qahvand plain are recommended.

Excessive abstraction of groundwater aquifers in the country has caused a sharp drop in the aquifer water level and the loss of aquatic aquifers, the effects of which is the phenomenon of subsidence. In this study, simulation of groundwater level changes in Marvdasht-Kharameh basin from a validation period and processing of a large set of raw data in Modflow mathematical model was used. The output results of sensitivity analysis of effective parameters in the calibration of Marvdasht aquifer show the maximum effect of hydraulic conductivity parameters and horizontal hydraulic conductance anisotropy and a set of linear groups of water supply network. Therefore, it is in line with the statistics of the Fars Regional Water Organization that there are wells with high discharge in these areas. According to the conditions of the aquifer, if the current operation trend continues, it is predicted that the groundwater level will drop by 15 meters during the years 2019 to 2029. Also, according to the average land subsidence, which averages 0.76 meters per 10 meters. The average land subsidence with the current harvest trend in the next ten years is predictable 114.78 cm and with a 30% increase in harvest, the rate of aquifer decline over the next 20 years is about 37 meters with an annual decline of about It is 1.9 meters. Land subsidence in this case is also predicted to be about 280 cm. Finally, according to the maps prepared from Marvdasht aquifer, due to the alluvial nature of the groundwater aquifer, the effect of water level drop can be observed from a short distance. The rate of subsidence in the southern and southwestern margins of the plain due to the low thickness of sediments and in the northern and northeastern parts of the plain due to coarse-grained sediments, is less than the central parts of the plain.

Soil erosion is one of the environmental problems that pose a threat to natural resources, agriculture and the environment. Quantitative assessment of erosion and sediment using erosion and sediment estimation models is one of the solutions through which erosion and sediment can be controlled to some extent and its amount minimized. In the present study, the aim is to predict the annual soil loss potential and sediment load. To predict these cases, the Revised Universal Soil Loss Equation (RUSLE) has been used in the context of the GIS. The amount of annual rainfall erosivity factor was calculated using 22-year monthly rainfall data at 18 stations around the basin. Its spatial variations were then estimated using conventional kriging. Soil erodibility index was obtained from soil map, which was prepared using field survey and remote sensing data. The topographic factor was extracted from the digital elevation model with a spatial resolution of 30 m. The annual vegetation factor was also estimated from remote sensing data. Since soil protection operations are insignificant in the study basin, the amount of soil protection factor was considered 1 throughout Basin. In this study, the mean values ​​of R, K, LS, C and P factors were equal to 264 MJ mm ha-1h-1y-1, 0.35 Mg ha h ha-1MJ-1mm-1, 2.00, 0.51 and 1. The average annual sediment yield in the study basin was estimated to be 16.137 th-1y-1, which was close to the value obtained from the sediment measuring station of the basin outlet (16.58 tons per hectare per year). The results of the erosion map in this model show that most erosion is located in the western and middle part of the basin. Because this region is composed of unstable formations and prone to erosion. The steep slope of the region, in addition to rainfall and land use change in this area, has faced many areas with soil erosion crisis. According to the results, the largest area of ​​the basin is related to the very low, low and medium erosion class, which is generally distributed throughout the basin, and the lowest basin area is in the high to very high erosion class (20%). Due to the fact that 20% of the study basin is in the high to very high erosion class, the need for protection measures in these areas is mandatory. The results of this study also showed that LS factor with a correlation coefficient of 0.81 had the greatest effect on estimating annual soil erosion by RUSLE model. This study proved the effectiveness of RS and GIS for quantitative estimation of soil erosion amounts, sediment yield and also erosion management.

Recent studies on the catastrophic consequences and widespread human and financial losses caused by natural disasters, especially earthquakes, show that no effective measures have been taken in this regard. One of the earthquake-prone areas of Hamadan province is Nahavand city, which is also one of the widest plains in the province. In this regard, the present study aims to zone the vulnerability of settlements to earthquakes using FAHP and GIS methods. For this purpose, 14 criteria which are soil texture, magnitude, centers of previous earthquakes, hazardous facilities, main and secondary roads of the region, rivers, geological layers, landslide position, slope, soil erosion, land use, regional faults, digital elevation model and Population points were used. In this regard, a zoning map of the settlement's vulnerability to earthquakes has been prepared for environmental analysis and assessments. According to studies conducted by other researchers around the world, in this study, to overlay the weight of criteria in fuzzy space, the gamma function with initial values of 0.5, 0.7, and 0.9 was used; after validating the results and reviewing their values, a gamma of 0.9 was selected and used in the present study. Results of Nahavand in 5 classes, with very low vulnerability potential in the area of 25065 hectares, relatively low potential in the area of 48173 hectares, medium potential in the area of 39000 hectares, relatively high potential in the area of 25571 hectares, and very high potential in the area of 13980 hectares he does. The results show that 28 villages are in the area with high vulnerability potential and 3 cities and 26 villages are in the area with relatively high vulnerability potential.

The Bakhtegan and Tashk lakes, as the second largest lakes in Iran, have been faced with a drought since 2007. Consequently, the ecology of the region has been disrupted and the social, health and environmental problems have been appeared. The purpose of this study is to investigate the role of meteorological and hydrological droughts on the drying up of these lakes. For this purpose, temperature and precipitation data measured at 21 rain gauge stations, flow rate measured at three hydrometric stations and the area obtained from the calculation of the normalized water differential index by processing 46 Landsat satellite images. Pearson correlation coefficient was used to determine the relationship between variables and linear regression method was applied to examine the trend each variable time series. Also, to determine the effect of climatic drought and hydrology on changes in the area of lakes, standardized 12-month rainfall and runoff indices were used. A decreasing trend has been discovered in the lakes area since 2008, and most of the lakes have been dried after 2012. Despite an increasing trend in the basin temperature (0.04°C/year), no significant change in this trend was observed in 2008. Moreover, decreasing trends have been detected in precipitation and discharge of the Kor River (the most important inlet of lakes), especially since 2007. The calculated standard precipitation and runoff indices indicated occurring of meteorological and hydrological droughts in the basin since 2008. Precipitation during the drought period decreased by 47%, but the discharge of the river into the lakes decreased by more than 95%. According to the results of this study, although rising in temperature together with the meteorological and hydrological droughts have caused reducing of the lakes area, but other factors could play an important role in this hazard. To determine the role of other effective factors, considering the role of human factors (especially agricultural development and dam construction) is also suggested.

Snow is considered as one of the climatic elements of water supply for life. Therefore, this study was conducted aimed to investigate the trend of changes in snowmelt in Iran and its impact on changes in the Mediterranean wave of westerly winds. For this purpose, we provided snowmelt and geo-potential height data of 500, 600, and 700 hPa atmospheric levels from the European Center for Medium-Range Weather Forecasts (ECMWF) version ERA5 with a spatial resolution of 0.25 * 0.25 ° for 1979-2019 January, February, March, April, November, and December. First, the trend and slope of monthly snowmelt changes in Iran were evaluated using non-parametric Mann-Kendall statistical tests and Sen.’s slope estimator. Then, using the percentile method, 25% and 75% percentiles of monthly snowmelt values in Iran were determined. The relationship between the changes in the Mediterranean wave of the westerly winds and the months with snowmelt values lower and higher than 25% and 75% percentiles was measured. Finally, the Middle East Synoptic Index (MESI) and decade expansion were used to analyze the impact of the monthly decreasing trends of snowmelt of the Mediterranean wave changes of the western winds in Iran. The results showed that in January, February, March, April, and December, the mean monthly snowmelt in Iran has a decreasing trend. In addition, a relationship was between the Mediterranean wave heights of the westerly winds in January, February, March, November, and December with the mean snowmelt of lower and higher than 25% and 75% percentiles, respectively. Also, the results showed changes in the height of the Mediterranean wave of westerly winds. It seems that these changes are among the factors affecting the decreasing trend of snowmelt in Iran, which is especially evident in the third and fourth decades (since 1999 onwards) in January, February, March, November, and December.

In recent years, with the increase in population, the quantity and quality of surface water resources due to human activity have changed. By studying the effects of land-use change on surface water resources, we will be able to understand the interactions between land use and water quality. Therefore, the purpose of this study is to evaluate the surface water quality in the Mehran plain watershed affected by land use. In this study, after extracting land use, the percentage of each land use area in the region for four time periods of 2000, 2007, 2016, and 2020 was determined, then the effects of land-use changes in both wet and dry periods on water quality parameters including anions, cations, SDR, TDS, EC were examined. Finally, Schuler and Wilcox's diagrams were used to determine the drinking water quality parameter. The results showed an increase in barren and urban lands compared to agricultural, rangeland, and forest lands. So barren and urban lands have increased by 13.2% over 20 years and the number of anions compared to the long-term average of 10 years is 14.82% and cations are 21.23% and soluble salts of SDR, TDS, EC is 36.9%, respectively, Increased by 18.35 and 18.30 percent. In most of the studied applications, the trend of changes based on the Mann-Kendall test showed an increase, and based on Pearson correlation between river flow and quality parameters with all parameters has a negative and inverse relationship, which with decreasing river flow, the trend of quality parameters increased. Is. According to Schuler and Wilcox's diagrams, water is in the salinity range for the study area. The results showed that the increase in human activities and climate fluctuations are factors affecting the water quality of the Gavi River, therefore, there is a need to manage programs to control land-use change.

Floods are among the hazards that affect millions of people around the world every year. The northern region of Iran has also faced numerous floods in recent decades and has caused a lot of damage to urban and rural areas. The northern regions of Iran have also experienced numerous floods in recent decades and have caused extensive damage to urban and rural areas. This study aimed to prepare a map of flood-prone areas by fuzzy method and to validate various maps downstream of the Neka River catchment in eastern Mazandaran. After the flood of 2019, the location of the areas that were affected by the flood was recorded in points. Data were randomly divided into two parts: training and validation 70% and 30%. Based on 70% of the observational data, fuzzy relationships of different information layers were determined, including elevation, slope, distance from the river, precipitation, lithology, and land use. After fuzzification of layers, using 9 different fuzzy operators, the layers overlapped and flood hazard maps were obtained. The validity of the resulting maps was performed using 30% of flooded points and the same number of non-flooded points by ROC method and Cohen's Kappa index. The results showed that operators of fuzzy Gamma 0.9, 0.8, and 0.7, had the highest accuracy of respectively. According to the map of the fuzzy Gamma 0.9, 15.7% of the area is in the very high and high class and 30% of rural and urban areas of the catchment are in these danger zones.

Evaluation and zoning of soil erosion using models that are more accurate, helps to implement conservation activities and control soil erosion within the watershed and reduce the amount of sediment outside it. The aim of this study was to zoning the soil erosion intensity of Baladeh watershed using RUSLE and ICONA models and toa investigate their accuracy with observations and terrestrial reality values. RUSLE model factors including rainfall erosion (R), soil erodibility (K), topography (LS), vegetation (C) and conservation operations (P) were calculated from rainfall data, soil map, digital elevation model and remote sensing techniques, respectively. In ICONA model, soil erodibility map was obtained by combining two layers of slope and rock surfaces. Then, in order to prepare soil conservation layer, vegetation index and land use layers of the area were overlapped and by combining erosion and soil conservation layers, erosion zoning map was prepared with this model. The accuracy of these models was evaluated using statistical indices and BLM method, all of which were obtained during field observations. For this purpose, a map with 2500 points was prepared as regular networking for sampling the maps obtained from the models and accordingly, RMSE statistics (root mean squares error), MAE (mean absolute error), MSE (mean squares error) and NSEC (Nash-Sutcliffe Model Efficiency Coefficient) were calculated. The results of the mentioned statistical indices and the errors of the models shows that the mentioned models are not sufficient in baladeh watershed, but the efficiency and degree of adaptation of the erosion classes of ICONA model with BLM output as reference map is higher, because the amount of RMSE, MAE and MSE is lower and NSEC is closer to number one.

Sistan and Baluchestan provinces and especially Sib and Soran cities have been affected by drought for many years. Most of the effects of this crisis have affected the agricultural sector, especially in rural areas. The occurrence of drought in this city has many direct and indirect effects on the lives of villagers and, certainly, it is not possible to prevent the occurrence of this phenomenon in terms of natural factors and the occurrence of droughts; Therefore, the first step to deal with and reduce the economic and social effects of the phenomenon will be to know and accurately understand the management factors on the occurrence and intensification of this phenomenon. With this knowledge, the study investigated this issue in rural areas of Sib and Soran cities. Quantitative research is practical in terms of purpose. Because the goal of the research is to achieve rules that are used in real and practical situations and help to improve executive methods. 19 villages and based on Cochran's formula, 300 families were selected as a sample. Data collection on two questionnaires; First questionnaire was to identify the consequences and spatial effects of drought and the second questionnaire was in the form of the Delphi technique to determine the effective management factors and strategies for drought. The risk of drought in rural areas has had negative social, environmental, and economic consequences. The spread of false and illegal businesses, the depletion of springs, wells, and surface water resources, as well as the instability of residents' livelihoods have been among the most important negative consequences of drought. On the other hand, lack of job diversity and lack of government investment is the most important management factors in aggravating the effects of drought, in which changing the pattern of water consumption and its storage as effective solutions were obtained.