جستجوی مقالات مرتبط با کلیدواژه "توزیع مکانی" در نشریات گروه "آبخیزداری، بیابان، محیط زیست، مرتع"

Land surface temperature is a parameter that affects many natural and human processes. In this study, the spatial distribution of surface temperature in Zanjan province from 2001 to 2023 was investigated. In addition, the effects of elevation, longitude, and latitude on the temperature distribution of the land surface, its spatial pattern, and the temperature zones of the province were evaluated and revealed using partial correlation methods, G* statistic, and clustering analysis, respectively. The results showed that the mean temperature of the land surface is 24.6 C° during the day and 5.3 C° at night. The relationship between elevation, longitude, and latitude with surface temperature is negative. elevation has the greatest effect on temperature, but the effect of latitude and longitude is weak. However, the temperature decreases by moving from south to north, west to east, and from lowlands to high elevations. The land surface temperature in the province follows a cluster pattern with a certainty of 95% or more, in which the lowlands and heights of the province have played the most role in its formation; Also, the province can be divided into four temperature zones, where the direction and boundaries of the zones follow the shape of the land. The mean daytime land surface temperature of the earth in the first group is 23.9 C°, the second group is 27.3 C°, the third group is 28.8 C°, and the fourth group is 18.8 C°. In addition, the mean temperature at night in the first group was 4.4 C°, the second group was 6.9 C°, the third group was 12.1 C°, and the fourth group was 1.9 C°.

Currently, drought poses a significant threat to food security due to reduced rainfall and increased agricultural demand. Its impact is particularly severe in arid and semi-arid regions, where populations are more vulnerable. Drought affects groundwater systems by initially lowering water supply, followed by a decline in groundwater levels and discharge. Compared to other types of drought, characteristics such as duration, intensity, and frequency alter groundwater systems.

Given the critical need for drought assessment and monitoring, this study investigated drought conditions in 12 areas within the Daranjir Watershed from 2002–2003 to 2017-2018. The watershed spans approximately 50,736.44 km² across Yazd and Kerman provinces, with elevations ranging up to 1,857.90 meters. Highlands cover 58.99% of the area, while plains cover 40.99%. Data on groundwater levels from observation wells were obtained from Iranian Water Resources Research Organization (Tamab) and regional water organizations in Yazd and Kerman provinces. Average monthly groundwater level values were then extracted from maps using inverse distance weighting interpolation in MATLAB. Groundwater drought conditions were subsequently calculated based on the Groundwater Resources Index (GRI) in MATLAB.

The GRI index calculations revealed severe droughts in Daranjir, Bardsir, and Qaryeh al-Arab deserts, with deficits of 81.38, 77.75, and 75.66, respectively. Qaryeh al-Arab experienced the longest drought, spanning 121 months, indicating the area's high intensity and prolonged drought conditions compared to other study areas. Mild droughts were the most frequent after normal drought across all study areas based on GRI index class frequencies.

Due to insufficient and highly variable atmospheric precipitation, drought is inevitable, especially in arid and semi-arid climates. Understanding drought severity and its impact on ecosystems is crucial for effective watershed resource management and optimal resource utilization. Continuous monitoring of groundwater levels due to drought and preparation of a comprehensive atlas for other watersheds in the country are recommended. Additionally, comparing drought conditions using appropriate models is essential. Short and long-term strategies are advised to mitigate this natural phenomenon, such as expanding greenhouse crop cultivation, utilizing drought-resistant crop varieties with high water efficiency, adopting pressurized irrigation systems, and implementing infrastructure projects to enhance groundwater and surface water storage, such as cement dams, reservoirs, and floodwater spreading systems in the study area.

Gully erosion contributes severe land degradation. It is therefore, necessary to identify the aggravating factors and to provide for sensitive areas to gully development. The aim of this study was to determine the spatial and climatic distribution of gully in Kermanshah Province, Iran and to identify the morphological characteristics and the main factors of their development. First, using 1: 20,000 and 1: 50,000 aerial photographs, the predominantly gully areas of the province were identified and then this information was corrected using field suevey. The climatic zones of the gully areas are identified using existing maps and modified by the Domarten Method. In each climate, one to three gully areas were identified as targets and in each of them a gully was identified and two replications were identified. The gully chanel chrectreristices were location, landuse, dimensions at the head-cut, intervals of 25, 50 and 75%, slope, width, length and cross section. The results showed that 17% of areas in the Kermanshah Province was affecterd by gully erosion comprising eight sub-climate classes. Dominat topographic conditions of gullies were developed at hilly and gentle plain areas with Trapezoidal cross section. The cross section indicated deep and V-shaped gully in marl formations (Fars group). These areas included Sarfiroozabad, Somar and Jabbarabad where most of gully measures were deeper and wider than other parts. Among the effective factors in creating and expanding the gully, we can mention heavy rainfall, slope, soil erodibility and destruction of vegetation upstream of the basin as natural factors and change of land use and improper exploitation as human factors in developing gully erosion.

Due to the limited number of meteorological stations especially in mountainous areas, the use of satellite data to extract rainfall is very important. On the other hand, the lack of spatial appropriate rainfall data is one of the major challenges in flood or drought prediction and timely warning in this case. One of the available solutions in this case is to measure rainfall from space.

The aim of this study was to investigate the accuracy of rainfall data obtained from TRMM satellite images in Taleghan watershed on a monthly and annual time scale during the period 2010 to 2015. For this purpose, TRMM images with three-hour spatial resolution were received during the statistical period for the study area. Then using the sum of three hours rainfall, daily rainfall was estimated. In the following the adjustment coefficients were also presented to reduce the error of rainfall data, and finally the accuracy of satellite image data was compared with two common interpolation methods i.e. invers distance weighting and Kriging.

The results of error indices showed that the rainfall of TRMM images is well correlated with the data of ground stations, especially Joestan station, but in some months, there is a problem of under-estimation and over-estimation. For this reason, correction coefficients were applied to solve this problem, which on average in most months; this coefficient was calculated less than one, which indicates the overestimation of TRMM image precipitation data. Examination of the corrected data showed that by applying the estimation coefficients, in addition to solving the overestimation problem, the error rate was also reduced and the Nash-Sutcliffe performance index was somewhat improved. The root mean square error (RMSE) at Garab station also decreased from 88 to 26 mm in annual rainfall time scale by applying the adjustment coefficients, which indicates an increase in data efficiency after the application of correction coefficients. The results of comparing the modified data with interpolation methods showed that in all error indices, the modified TRMM data is more efficient in estimating rainfall.

Overall, it can be said that rainfall from TRMM images can give satisfactory results if adjustment coefficients are applied, and in areas with a shortage of meteorological and data stations, it can be a reliable source of rainfall data.

This study was conducted with the aim of understanding the temporal and spatial variations of groundwater levels in the Meshgin Plain Aquifer, located in Ardabil Province, with the application of spatial statistics and temporal regression and using groundwater depth data on an annual scale from 2007 to 2016. In order to achieve the optimal method of zoning spatial changes in groundwater level, a comparison of different interpolation methods including Radial Basis Functions (RBFs), Inverse Distance Weighted (IDW), and Kriging (KRG) based on cross-validation was used. In addition, regression relationships between groundwater level and the study years were fitted to determine how the data series ascended or descended. A comparison of interpolation methods based on cross-validation showed that the root mean square error (RMSE) of RBF, IDW, and KRG methods were 21.98, 22.85, 22.57 in 2007; and 23.45, 27.88, 26.25 in 2016, respectively. Therefore, the RBF method with the lowest estimation error due to the power applied to scattered data and low sampling points in both years was selected as the optimal method for estimation of groundwater level in the aquifer. The weighted average of groundwater table loss was calculated as equal to nine meters. Furthermore, the iso-decline map of groundwater level was indicative of a decrease in groundwater level in the western half and its increase in the eastern half of the aquifer which is related to anthropogenic factors (withdrawal of groundwater in agricultural lands). In general, it can be stated that the accuracy and efficiency of interpolation methods depend on the region and data characteristics. In the case of Meshgin Plain Aquifer, the discharge factor has been more effective than the recharge factor in annual fluctuations of groundwater level. Accordingly, it is necessary to establish a balance between the pattern of cultivation and irrigation and the pattern of spatio-temporal variations of groundwater level in managerial plans for Meshgin Plain Aquifer.

Zoning of gully erosion susceptibility and determining the factors controlling gully erosion is very important and vital. The aim of this study was to investigate the spatial distribution of gully erosion using two models of ANN and MaxEnt and to determine the factors affecting this type of erosion in Golestan Dam basin. Therefore, 14 factors in the form of three divisions, including topographic factors, other factors and combination of factors (14 factors) were considered as predictors of sensitivity. Out of 1042 gully erosion points, 30 and 70 percent were randomly classified as validation and test data, respectively. The results of Jackknife test showed that the parameters of height, rainfall and depth of valley are the most important variables affecting the prediction of gully erosion. The results of the modeling showed that the best accuracy of the model based on the ROC curve in the training model (0.923) and in the validation, stage (0.902) was the artificial neural network model, and this condition is achieved when all the factors in the modeling be involved. According to this model, about more than 20 percent of the domain (45633 ha) has a high sensitivity and is very susceptible to gully erosion.

One of the most important last century challenges in the world was drought and monitoring and assessing drought severity and duration to combat and mitigate its impacts is very necessary. In recent decades, with developing of remote sensing issues, satellite-based estimating drought with high spatial resolution and different time steps were widely used. Hence, the aim of this study was focused on the analyzing drought and error distribution of TRMM satellite data-based estimation with ground data over the period 1998 to 2014. In this regard, in order to assess the accuracy of meteorological drought index based on the TRMM satellite data, 41 synoptic stations were used in Iran. In this study, error assessment criteria were included NSE, RMSE, ME, Bias and correlation coefficient and also the IDW interpolation method in ArcGIS 10.3 was used for spatial analysis. Results of drought index showed that in terms of severity, Kerman, Bushehr, Kashmar, Ghazvin, Bojnurd, Kashan stations have suffered from at least one extreme status for 1998 to 2014 and in terms of frequency, the most frequent drought was in Karaj station. Results of spatial analysis of error criteria  showed that the drought index estimated of TRMM satellite had the lower error in northeast of Iran (around Mashhad and Kashmar stations) and southwest of Iran (around Shahrkord, Esfahan, Yasouj, and Shiraz stations) while the most error was in central region of Iran (around Biarjomand, Tabass stations), respectively. In most areas of the country, drought index estimated by TRMM data had acceptable agreement with ground stations data. Calibrating the TRMM data with ground stations can be used for drought monitoring in areas without stations for networks 0.25*0.25 latitude and longitude degrees.

Dust phenomenon has now become one of the emerging natural hazards in the country, a phenomenon that affects its natural and human conditions with its harmful effects on different aspects. Therefore, in this research, the temporal –spatial distribution of dust in west and southwest of Iran and at meteorological stations located in three provinces of Eilam, Khuzestan and Kermanshah were investigated. For this purpose, the statistics of dust days was collected from the Meteorological Organization of Iran for the statistical period of 1986-2008. At first, the necessary data set was considered for normalization, and then the time distribution of this phenomenon at the level of the stations in the study area was determined in a graph. Further, according to the GIS and ArcGIS10.2 software, the distribution of the annual and monthly spatial days along with dust in west and southwest of the country based on different interpolation methods were determined. The results showed that the number of days with dust in Dehloran, Ahvaz and Dezful stations is at the highest level and in the southern provinces of Eilam and Khuzestan the most critical conditions are observed and from north to south of the region, the number of days of dust increases. Also, the results showed that the distribution of this phenomenon is not affected by regional climate systems due to topographic variation and altitude of the west of the country, and the most days with dust in the southwest are observed in Khuzestan province. In the western regions of the country, there is a high frequency in the middle of the spring. The spatial distribution of this phenomenon is more than the latitude and altitude elevation. According to the results, the criticality of the whole region is important, but in Khuzestan province, conditions are in a more critical situation. Managing a crisis before and during this natural hazard is important for better adaptation to reduce its harmful effects.

The lack of enough meteorological stations at high elevations in mountainous regions causes a limitation for using regression relations to interpolate air temperatures at different time scales. Therefore, in this study, geostatistical methods include Kriging, Co-Kriging and Weighting moving average has been compared with elevation-temperature relation using a data series of 25 years (1975-2000). Evaluating the selected interpolation methods has been done based on Root Mean Square Error, Mean Absolute Error and Mean Biass Error. Also the physical conception of estimated values has been analyzed based on extracted maps. Results showed that using elevation as a covariate in Cokriging method caused a 28% increase in effective range. Although Kriging method overestimate the monthly and yearly air temperature, no significant difference was observed in evaluating indices between Kriging and Cokriging methods. Results also demonstrated that both Kriging and Cokriging method could be used instead of linear regression to interpolate air temperature in the study area. Analyzing prepared maps showed a decreasing pattern in air temperature from east to west parts.

According to the importance of groundwater resources in providing of human needs, lack of control and inappropriate management of these resources can lead to the problems such as nitrate pollutions arising from the use of chemical fertilizers in agricultural lands. With generalized point data to the area using the geostatistics methods can be determine the pollution content in areas without sampling. This research was conducted with aiming to zoning the groundwater nitrate pollution content in some of Andimeshk agricultural lands. For this purpose, samples were taken from 55 wells and nitrate content was obtained in each of the wells based on mg/lit nitrate. Geostatistical methods that were used include kriging, cokriging and inverse distance weighting. After normalization of the data and drawing the variogram, kriging method (i.e. RMSE: 1.4) with fewer errors than the cokriging (i.e. RMSE: 1.42) and IDW (i.e. RMSE: 1.46) was chosen as the appropriate method of zoning. Finally, the nitrate zoning map was drawing by using geographical information system. Nitrate maps can be used as an important tool for decision makers in the field of management.

Heavy metals are very important from environmental consideration due to their toxicity and accumulative properties. The aim of this study is the evaluation of spatial distribution of Cr, Co and Ni in the surface soils of Hamadan province. For this purpose, the surface soil samples (0-20 cm) were collected using systematic random sampling method and the concentration of heavy metals and some of the soil parameters such as pH, EC, the percentage of organic matter, sand, clay and silt were analyzed. For interpolation and mapping the spatial distribution of heavy metals, the accuracy of Kriging methods and their models were compared by the Mean Absolute Error (MAE) values and Mean Bias Error (MBE), and the method with the lowest error was selected. Maps of chromium and nickel distribution were prepared by ordinary Kriging with a spherical model, and that of cobalt by disjanctive Kriging with exponential model. The western regions of Hamadan province had the highest concentration of chromium, cobalt and nickel. According to obtained maps, the regions with the highest concentrations of heavy metals corresponded to the igneous and metamorphic bedrocks. It seems that the geology is the main factor influencing the concentration of heavy metals in the soil.

Spatial and temporal distribution of qualitative factors of groundwaters is important to preserve their quality. So, one of the advanced techniques for distribution of groundwater’s qualitative is geostatistic methods. In this study, 33 active wells were randomly sampled to determine the spatial distribution of nitrate pollution in groundwater of the Siakh Darengoun Region (West of Shiraz in Fars Province). According to the results, nitrate concentration in the studied region is between 3.85 to 14.92 mg/l. Three methods such as Kriging, Inverse Distance Weighting and Cokriging were used for studying nitrate spatial changes. Furthermore, Kriging Indicator was used to produce the map of nitrate pollution probability. The maps can be used as an efficient tool for management decisions.

Flood risk estimation is one of the most important subjects for Hydrologists. The main objective of flood risk estimation is study on past events in order to determine the following flood risk. There are various methods for flood risk estimation. Rainfallrunoff and empirical equations are the most recently used methods. In these methods, rainfall is the main parameter influencing flood mechanism. In this research, spatial distribution of rainfall pattern in Esfahan province is studied. Esfahan province with 10.5 million ha area is located in central part of Iran with different topography, climate and ecological condition. A number of 203 rainguages, located in the study area and nearby, were studied. Recorded data of 32 years, from 1968-2000 and a total number of 1654 storm events with less than 1 hour to 72 hours duration were investigated and three index events, i.e. widespread and maximum events, were used. The common methods of geostatistics like kriging, Co-kriging, IDW and TPSS were applied to interpolate the recorded points to non-observed ones. Results showed a low correlation between rainfall and elevation in the study area. Among the studied interpolation methods, kriging showed the best results, from which the Gussian and Spherical models best fitted to the observed points. In order to gain best results, it is recommended to add the number of rainfall gauge sites according to the World Meteorological Organization (WMO) standards. Also, grouping the study area into homogeneous regions and studying DAD in each homogeneous region is advised.