جستجوی مقالات مرتبط با کلیدواژه « semi-arid regions » در نشریات گروه « جغرافیا »

For this purpose, the data of 13 climatic variables in 14 synoptic stations in a period of 44 years (from 1977 to 2020) used and a 13x14 matrix (rows; climatic elements and columns; number of stations) was created. In order to generalize the station data to the area, a grid with 15x15 km pixel was formed in central Iran and a matrix with dimensions of 446x15 (rows; digital pixel and columns; number of stations) It was found that the basis of the calculations will be factor analysis with varimax rotation and cluster analysis with Ward integration. The results of measuring the relationship between altitude and climatic variables indicate that in Central Iran, there is a direct and significant relationship between these two factors. However, due to the influence of local and macro-scale climatic factors, this relationship is not the same throughout the area and sometimes creates climatic nesting. In addition, the results showed that the 4 main and effective factors that make the climate of central Iran are: precipitation, temperature, humidity and dust storm. These factors explain 86.2 percent of the climatic behavior of this area. So that the rainfall with 35 percent is the most important climatic element in this area, which often dominates in cold mountainous regions and high altitudes. The temperature is 27.3 percent in the central deserts and the sides of Lut desert in Kashan, Khourbiabanak, Lar and Bam. Humidity is effective with 15.3 percent in parts of hot and humid southern areas in Baft, Abadeh and even cold and humid northern areas in Daran, Isfahan. Dust storms with 8.8 percent are the least effective factor in the climate of central Iran, which are scattered in Khourbiabanak, Bafaq, Yazd, and Kashan

Atmospheric aerosols are a colloid of solid particles or liquid droplets suspended in the atmosphere. Their diameter is between 10-2 to 10-3 micrometers. They directly and indirectly affect the global climate by absorbing and scattering solar radiation, and they also have a serious impact on human health by emitting harmful substances. In addition, high concentrations of aerosols on a local scale due to natural or human activities have adverse effects on human health, including cancers, pulmonary inflammation, and cardiopulmonary mortality. Monitoring the temporal and spatial variability of high concentrations of aerosols requires regular measurement of their optical properties such as aerosol optical depth (AOD).

Algeria is a large country with little knowledge of the spatial and temporal diversity of AOD, and the low spatial resolution of existing products makes it very difficult to predict aerosols (airborne particles) at the local scale, especially in arid southern regions. As a result, AOD recovery with data with higher spatial resolution is crucial for determining air pollution and air quality information. Several AERONET stations have been installed in Algeria. The Tamanrasset_INM station has been selected based on its location and the availability of historical AOD data for the period (2015-2016).
In this study, Landsat-8 / OLI image from tile 192/44 was used for satellite images. To this end, 23 TOA-corrected L1G-level Landsat-8 / OLI cloudless scenes were downloaded from January 2015 to December 2016 in the study area. DN values ​​are converted to TOA reflections using the scaling factor coefficients in the OLI Landsat-8 metadata file. In this study, the minimum monthly reflectance technique was used to recover AOD in this area. As a result, LSR images were used in the recovery process in different months of 2015 and 2016. The process of selecting reference LSRs was initially based on the selection of clear, foggy / cloudless sky images. The selected images were then used to construct artificial images in which each pixel corresponds to the second lowest surface reflection of all selected monthly images to be the LSR pixel for the respective month. The AOD retrieval method developed in this study is based on a LUT, using the 6S radiative transfer model. The advantage of using the 6S model is its ability to estimate direct components and scattering using a limited number of inputs for each spectral band in the entire solar domain. The effect of the viewing angle is limited because Landsat data are usually obtained with a fixed viewing angle. Surface reflectance can be estimated from a pre-calculated LSR database. The accuracy of AOD recovery depends on the use of the appropriate aerosol model. A continental model was selected from the available aerosol models. Other atmospheric parameters such as ozone, carbon dioxide, carbon monoxide and water vapor are considered by default. The AOD values ​​used to make LUT are set as follows: 0.0, 0.05, 0.1, 1.5, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.0, 1.2 and 1.5. The zenith angles of the sun and the sensor range from 0 to 70 degrees with a step of 5 degrees and the range of azimuth angles from 0 to 180 degrees with a step of 12 degrees. Using these parameters, the radiative transfer equation was run in forward to obtain the TOA reflection. Different combinations of input and TOA output parameters are stored in LUT. AOD retrieval is based on a comparison between the TOAs estimated with the model and the observed items using the best fit approach. Using such an approach, the estimated AODs are simulated in accordance with those used in the production of TOAs, using a competency function that minimizes the distance.

In this study, the AODs recovered at 550 nm in a 5-by-5-pixel window around the AERONET site were averaged. The considered AERONET values ​​are the average of all measurements taken within ± 30 minutes of image acquisition time. Observation regression results (AOD from Landsat 8 images and AERONET stations) showed that the correlation coefficient is about 84%. This study shows a good fit of the model on the research data and shows the high capability of the model. This study showed a strong recovery of AOD against AERONET data of more than 70% at . The differences can be attributed to a limited number of points or hypotheses related to the aerosol model used in this study. The assumption of using a pre-calculated LSR does not limit the accuracy of this method because we have shown that in arid regions where the change in land cover in different months of the year is small, a pre-calculated LSR image can be representation used the share of surface reflection in the radiative transfer model throughout the month.

In this study, an AOD derived from a high-resolution satellite at an urban scale was produced in the city of Tamanrasset, Algeria. The developed method assumes that the change in land cover is minimal and the temporal change in LSR is not significant. A pre-calculated LSR image is created to show the surface reflection in the retrieval process. Based on the 6S radiative transfer model, an LUT was constructed to simulate the TOA reflection of the built-in LSRs and a set of geometric and atmospheric parameters. The retrieved AODs were compared with the AERONET ground data. The results show that this approach can achieve reasonable accuracy in AOD recovery, which reaches about 70.9% at . In addition, this approach is suitable for estimating AOD in urban areas compared to existing AOD products with low spatial resolution. The results of this study show a 4% improvement compared to the results of Omari et al. (2019). The results of this study showed that ignoring the monthly changes in LSR values leads to good results in AOD recovery.

Drought is a natural phenomenon that has a significant impact on agriculture and also influences different aspects of people's lives in both arid and semi-arid regions. Vegetation cover is one of the living components of the ecosystem and plays an important role in many ecosystem processes that are strongly affected by climatic events such as drought. In the present study, the status of vegetation changes in relation to drought index has been investigated in the Ilam catchment (Ilam city). In this research, the 30-year precipitation of synoptic stations of Ilam, Mehran, Dehloran, Sarableh, Ivan, Darrehshahr and Abdanan were applied to calculate the standardized precipitation index (SPI). The Landsat satellite images were used to extract the standard vegetation difference index (NDVI) and also to investigate the detection of vegetation changes in the study area. Besides, the relationship between the SPI drought index and NDVI vegetation index was performed by the Pearson correlation method between raster layers of NDVI and SPI. The results of the SPI index showed that the drought in the years 2003 and 2008 occurred with more intensity than other years. Moreover, the vegetation classification map obtained from the NDVI index showed a decreased trend in the level of vegetation from 1988 to 2018 which is occurred mostly in the dense vegetation category (15959 ha in 1988 and 6492 ha in 2018). Based on the results of the present study, it is concluded that the changes in vegetation over time is directly related to the severity of drought, which should be considered by managers and decision-makers in the natural resources for vegetation management.

Land vulnerability one of the major global challenges as an objective case of degradation of arid, semi-arid and semi-humid ecosystems caused by natural processes and human activities. However, in order to assess the vulnerability of the land, it is necessary to know exactly the degree of tolerance of ecosystems and the use of indigenous knowledge systems to external conditions.The present study was based on the IDI hybrid index algorithm to assess the severity of Khorasan Razavi vulnerability over a 16-year period (2001-2016). For this purpose, two indicators of vegetation status (VCI) (MOD13Q1) and temperature status (TCI) (MOD11A2) based on the opinion of experts, and according to the availability of these indicators, based on satellite data and in The desired time period was selected. Then, the images of Modis sensor products were prepared and normalized, and the indices were scaled in the range of zero and one, and the hierarchical method in EDRISI software was used to evaluate the weights. Using 250 ground harvest points, the accuracy of the model was determined using kappa coefficient for vegetation status. Then, using IDI combination model and implementation of the model, the area has very low vulnerability (0-15 . 0), low vulnerability (0.3-0.3), medium vulnerability (3.5-3.0) 0), high vulnerability (0.5-0.7) and very high vulnerability (1-7 . 0). The results showed that the highest vulnerability in 2001 with more than 50 percent of the province's average in the middle class and in 2016, the highest vulnerability in the two medium and high classes is approximately equal to the proportion of 44 percent. The overall accuracy of the model for the IDI combination model was 78.6% and the Kappa coefficient was 0.7.

In this research, in order to investigate the effect of short and long term observational data on the quality of predicting climate parameters, the LARS-WG6 statistical downscaling model is performed for EC-EARTH model and the optimistic scenario RCP4.5 and the pessimistic scenario RCP8.5. Also the HadGEM2-ES model with the optimistic scenario RCP2.6 and the moderate scenario RCP4.5 and the optimistic scenario RCP8. 5 are investigated. Forecasts are applied on the next three 20-year periods (2021-2040, 2041-2060, 2061-2061). Three daily statistical periods of the Drudzen Dam Synoptic Station including the 30-year period (1988-2017), the 20-year period (1998- 2017) and the 18-year period (1988-2005), were used. The 18-year period was determined by examining the 30-year trend. A fractal based procedure is employed for extracting a complete pattern of repeating weather events including rainfall, minimum and maximum temperatures. The modelchr(chr('39')39chr('39'))s capability in the simulation was measured according to the base period and the accuracy of the anticipations was evaluated using MAD, MSE and RMSE statistical tests. Studying the results clearly shows the effect of time scale changes on the accuracy of predictions. Accordingly the 20 year time period showed the least error, especially for the precipitation parameter. In general, it was revealed that this model predicts minimum and maximum temperatures with high accuracy and the rainfall prediction holds less accuracy. The prediction of models under different scenarios and different time intervals showed an increase in minimum and maximum temperatures. Moreover, the model indicates while the average annual precipitation increases in the coming years, the pattern of precipitation will change. In April, January and December, we will see an increase in precipitation and a decrease will be experienced in February.

Vegetation is one of the essential factors in structure and function of terrestrial ecosystem and it is one of the principal loops in water-soil-plant-atmosphere continuum. Several studies have demonstrated that vegetation covers are sensitive to alteration of climatic, edaphic, topographic and human activities. Thus, alteration in vegetation and its relation with the mentioned factors are important of high importance. In order to investigation of vegetation changes and its effective factors, the current study was conducted in Kharestan region placed in Fars province, Iran. In this regard, the images obtained from ETM Landsat 7 (2000-2017) and meteorological data gained from local and 17 regional meteorological stations were used. Using these images, temporal and spatial changes NDVI and NDVI anomaly were studied. A supervised classification method was used to extract land use map. Finally, the relationship of NDVI with climatic, topographic and anthropogenic factors was investigated. Relationship between NDVI and climatic and topographic factors was estimated using GWR and OLS methods, respectively. Generally, temporal variations showed a slow increasing trend in NDVI value. NDVI anomaly was mostly negative before 2008 but it turned to positive after 2009. NDVI spatial distribution showed an increasing tendency from north toward center and continued to south-west of the study area. The study shows that the vegetation cover change was caused by both natural factors and human activities. NDVI increased in agricultural and pasture lands. Also, natural vegetation has been affected by climatic factors more than irrigated vegetation (agricultural and gardens). Furthermore, vegetation variation influenced by topographic factors likes height, slope and aspect. Also, with an altitude over than 2500 m, NDVI showed a decreasing trend, on slopes lower than 5° it increased. NDVI values in north and east directions were higher than in southern aspects. The overall trend indicates an increase in temperature and a decrease in precipitation during the study period. The maximum positive and negative correlation between mean annual precipitation and NDVI using ordinary least squares method were 0.93 and 0.83, respectively. Also the maximum negative and positive correlation between NDVI and temperature were 0.65 and 0.5, respectively. The highest local R2 values between NDVI with precipitation and temperature were 0.45 and 0.44, respectively, which was observed in the central parts of the region. According to the obtained results through the present study, it can be stated that environmental factors like precipitation, altitude, slope and aspect are the Influential factors controlling vegetation in Kharestan (Fars province, Iran).

Study the behavior of the rivers at arid and semi arid areas is of the main and basic activities in the country (since a great portion of Iran has arid and semi arid climate). The main differences of arid areas from humid areas are the different climatic factors including the precipitation amount and pattern. This issue can cause the change of flow regime and sedimentation regime (FSR) and their ratios in these areas. Also temporary flood ways of arid areas, in which the water flow is limited to heavy rainy and wet seasons, has a great influence on flow and sediment regime (FSR). In this research, by statistical review of flows discharge in arid and semi arid areas at the west part of country, it is tried to review the effect of climate on flow and sediment regime.For this purpose, flood discharge with different return periods were estimated by the best statistical distribution of 21 hydrometric stations. Then by using rating flow of sediment, sediment amount was measured in different return periods. At the next step, flow and sediment regime was calculated and the relationship between flow and sediment regime and the area of relevant up stream sub-catchment areas was determined. Also the results of this study show that the relation of up stream sub-catchment areas of each station will increase with FSR increase in high return periods.