جستجوی مقالات مرتبط با کلیدواژه « نیم تغییرنما » در نشریات گروه « جغرافیا »

Soil penetration resistance (PR) and soil shear strength (SS) are used to evaluate soil erodibility. Some soil properties such sand, silt, clay, bulk and particle density, total porosity, organic carbon and CaCO3 and also some land characteristics such as percentage and direction of slope, altitude, type and density of vegetation can affect SS and PR. For example, PR values exceed 2.5 MPa, while root elongation is significantly restricted. Most of soil properties have temporal and spatial variabilities. Therefore, it is necessary to use geostatistical methods to simultaneously use quantitative information and geographic location of variables. The forest, range and cultivated soils of Fandoghloo region of Ardabil are located in sloping lands and are subject to erosion. Therefore, it is necessary to know the state of spatial variability of soil SS and PR as two important indicators affected by compaction and also effective on soil erosion in the mentioned area. The main objectives of this research were: 1) Investigating the spatial variabilities and drawing maps of soil SS and PR in forest, range and cultivated lands of Fandoghloo region of Ardabil,  2) Investigating the correlations between soil SS and PR with other soil characteristics in the study area,  3) Determining semivariogram parameters such as semivariogram models, spatial dependence classes and effective range for soil variables, 4) Comparison of the accuracy of geostatistical methods (ordinary kriging (OK) and  inverse distance weighting (IDW)) in the interpolation of SS and PR.

 This study was conducted in the forest, range and cultivated lands of Fandoghloo region of Ardabil located at the 25 km of Ardabil city, northwest of Iran (48° 32ʹ 45ʺ to 48° 33ʹ 5ʺ E and 38° 24ʹ 10ʺ to 38° 24ʹ 25ʺ N) at summer 2023. Totally, 80 geo-referenced samples were taken from 0-10 cm soil depth with 50×50 m intervals (15 ha) in cultivated (n=37), range (n=23) and forest (n=20) land uses. Sand, silt, clay, organic carbon (OC) and particle density (PD) were measured in the disturbed soil samples. Bulk density (BD) and field water content (FWC) were measured in the undisturbed soil samples taken by steal cylinders with 5 cm diameter and height. Total porosity was calculated using BD and PD. Soil penetration resistance (PR) was directly measured in the field at three replicates using a cone penetrometer. Soil shear strength (SS) was obtained using shear vane in saturation condition in the field at three replicates. The best fitted semivariograms model (Gaussian, spherical and exponential) was chosen by considering the minimum residual sum of square (RSS) and maximum determination coefficient (R2) for soil variables. Ordinary Kriging (OK) and inverse distance weighting (IDW) interpolation methods were used to analyze spatial variability of soil SS and PR. Spatial distribution maps of soil variables were provided by Arc GIS software. Normality test of data by Kolmogorov–Smirnov test and Pearson correlations were done using SPSS software. Figures were prepared using Excel software. The accuracy of OK and IDW methods in estimating soil SS and PR was evaluated by mean error (ME), mean absolute error (MAE), root mean square error (RMSE) and concordance correlation coefficient (CCC) criteria. The CCC indicates the degree to which pairs of the measured and estimated parameter value fall on the 45° line through the origin.

According to the results of coefficient of variation (CV) from the study area, the most variable (CV=58.3 %) soil indicator was PR in range land use, whereas the least variable (CV= 3.95 %) was PD in cultivated land use. The Pearson correlation coefficient (r value) indicated that there are significant correlations between OC with sand (r=0.59) and FWC (r=0.78) and between PR with SS (r=0.31). Also, significant correlations were found between PR with FWC (r=-0.45) and silt (r=-0.36) and between SS with OC (r=0.38), sand (r=0.48) and silt (r=-0.34). The spatial dependency classes of soil variables were determined according to the ratio of nugget variance to sill expressed in percentages: If the ratio was >25% and <75%, the variable was considered moderately spatially dependent; if the ratio was >75%, variable was considered weakly spatially dependent; and if the ratio was <25%, the variable was considered strongly spatially dependent. The strong spatial dependences with the effective ranges of 752 m was found for PR. The medium spatial dependences with the effective ranges of 787 m was obtained for SS. The silt and FWC variables had the least (636 m) and the highest (2282 m) effective range, respectively. The range of influence indicates the limit distance at which a sample point has influence over another points, that is, the maximum distance for correlation between two sampling point. The models of fitted semivariograms were Gaussian for PR and spherical for SS. The high values of CCC and low values of RMSE values indicated the more precision and high accuracy of OK compared with IDW interpolation method in estimating PR in the studied area. According to the RMSE and CCC values, IDW was better than OK to predict SS. Generally, the spatial maps showed that the highest values ​​of soil PR were observed in range land use and the lowest values ​​of soil SS were observed in cultivated land use of the study area.

Results showed that PR negatively related to the silt and FWC. Also, SS negatively related to the silt and positively related to the sand and OC. The strong spatial dependency was found for PR and medium spatial dependency was determined for SS in the studied area. The silt revealed the smallest effective range (636 m) among the studied variables. As a suggestion, for subsequent study, soil sampling distance could be taken as 636 m instead of 50 m in order to save time and minimize cost.

Rainfall is amongst the most important climatic elements with a lot of spatial and temporal changes; in contrast to the other climatic phenomena, rainfall features more notable movement complexity. The studies performed in this regard indicate that such a climatic element as rainfall features a non-stationary behavior with a vast part of this non-stationariness being the result of the rainfall’s being influenced by the spatial properties and the complex pattern of the spatial organization causes the emergence of complex behaviors in the precipitations. The importance of the rainfall as the country’s water resource and the daily increasing reduction of the country’s water reservoirs demands the study of the rainfall’s behaviors. In the present study and by the assistance of the methods of spatial statistics, the spatial pattern of the spring rainfalls in the northwest of Iran will be elaborated. 
Data and

The study area of the present study is the regions in the northwest of Iran (Azerbaijan-e-Gharbi, Azerbaijan-e-Sharghi, Ardabil, Kurdistan and Zanjan Provinces) and, to perform the study, use has been made of the monthly precipitation data acquired from 121 synoptic stations as well as climatological investigations and precipitation studies for a period between 1994 and 2014.In order to perform the spatial analysis of the precipitations, use has been made of the digital map of the elevation in the environment of ArcGIS software for extracting slope and dip. In the next part and in order to analyse the spatial structure of the rainfall and investigate the degree of similarity between the data acquired from 121 station points, use has been made of the half pseudo-variance spatial correlation index. The Semivariogram has been estimated based on the arithmetic mean of the intervals.In the present study, use was made of the longitude and latitude of every station point and the rainfall rates of every point for delineating the empirical Semivariogram for three months, namely April, May and June in the environment of Variowin Software, version 2.2; then, various theoretical models were estimated in terms of their goodness of fit and the exponential model was selected as the best model for every month.In order to analyse the spatial factors influencing the spring rainfalls in the northwest, the balanced geographical regression model was estimated in terms of its goodness of fit with its output being the indicator or indicators influencing the occurrence of spring rainfalls according to the explanatory variables of slope, dip, elevation and latitude.

Following the investigation of the data related to April, it was made clear that the effect of the elevations on the rainfall variations is significant in this month in the entire parts of the region. The highest significant effect of the elevation has been in the central parts of the region for such a reason as the large density of the mountainous masses in this part and the passing of precipitation systems from these regions. In parts of the region’s north (north of Azerbaijan-e-Gharbi, Azerbaijan-e-Sharghi and Ardabil), the significance rate of elevation is reduced because these regions are plains and plateaus and lower in elevation than the other areas. Latitude has been found having a significant effect in the southwestern sections of the region (south of Azerbaijan-e-Gharbi, Kurdistan and Zanjan) and, in a more scattered manner, in the north of Urmia Lake and it seems that the reason for such a significance is the passing of the precipitation systems from the southern sections of the region.As in April, the effect of the elevation on the rainfall has been also found significant in all the sections of the region in May. The highest rate of significance has been found centered in the western and central sections of the region (particularly in the central parts) and this is completely due to the existence of the mountainous air masses. Considering the gradual displacement of the western winds towards the northernmost parts of the region and the vertical irradiation of the sunlight onto the sun-facing foothills, the role of the elevations becomes more accentuated in the creation of convectional rainfalls and the regions with lower elevation would receive lower precipitations. In June, as well, except the south-eastern section of the region (eastern half of Zanjan Province), the other regions have been found with the significant effect of elevation on the creation of rain. In this month, the conditions fit the occurrence of foothill convection in the studied area. The highest effect of the rising and falling lands on the creation of the rain has been evidenced for the north-western sections and this is in match with the path through which the western winds pass on these days; that is because the rain-causing winds are present in this section in this month and, considering the region’s elevations, cause the occurrence of rainfall. The effects of latitude in June is like those in May and the presence of the western winds and setting of the ground for the foothill convention causes rainfalls in the northern and central section of the study region.

Elevation has been found influential in the entire studied region on the rainfall because the high density of high grounds causes the ascension and condensation of the humid air that causes rainfall. Besides elevation, the dip also influences the rainfall in Kurdistan and south of Azerbaijan-e-Gharbi because the orientation of the foothills in this section sets the ground for the dynamic ascension of the humid air. In Ardabil and north of Azerbaijan-e-Sharghi, slope is also an effective factor. The high slope of these regions causes the acceleration of the humid air masses’ ascension. The effects of the latitude on rainfall during spring are different and mostly related to the presence of the western winds; in April in Kurdistan and in May and June in Azerbaijan-e-Sharghi, latitude has been found with the highest effect on the rainfall.

Understanding the status of discharge and sediment of watersheds area provides an understanding of the hydrological processes. Uniform assuming of discharge and sediment in a watershed leads to the application of unit planning and management for the entire watershed and leads to a failure to achieve the goals. The present study was conducted with the aim of studying spatial variations and zoning of discharge and sediment values in Ardabil province during 10 years (2005-2014) at 37 stations with hydrometry in Ardabil province. IDW interpolation methods, simple kriging, ordinary kriging and cokrigring were investigated to determine the best method for studying spatial variaions, discharge and sediment variables. Based on the results of the evaluation indices of IDW (RMSE=1.172, MAE=0.644, MBE=-0.2, MSE=1.373) and cokriging (RMSE=0.107, MAE=0.08, MBE=-0.001, MSE=0.011) and the correlation coefficient between measured and estimated values by IDW (r=0.429) and cokriging (r=0.554) respectively, as the best method for evaluating the discharge and sediment variables were chosen. Based on the results of the IDW method, the amount of digestion in the Western parts of Ardabil province is greater (4.84-5.8 m3/s), and in the central section, this amount is the lowest (0.04-1 m3/s). According to the results of the interpolation of the sediment variable with the cokrigring method in the Western and Southern parts of Ardabil province with a higher amount of sediment (0.16-0.19 ton/ha/year) and in the central parts of the sediment deposition (0.01-0.04 ton/ha/year).

Importance of location factors substantially change the climatic phenomena and developments can be enjoyed. Influence of these factors can be strengthened, diluting and determine how the distribution of climatic processes be flashed as a result recognizing the role and relationships of these factors can lead to the understanding of the spatial patterns of climatic variables and the improvement of environmental planning. Accordingly, in the present study using monthly rainfall data of the synoptic station 121, climatology and rain Northwest of Iran in the period of assessment 1987 until 2014, and the use of the data, elevation, latitude, tilt and direction of tilt was trying features and relationships in spatial distribution and location factors of rainfall changes about the analysis. Therefore, the purpose of the center of the circle, half the average of the standard geographic change and even regression (GWR) was used. The results of the investigation showed that during the month of October due to the low amount of variance in the Western region, winds, rainfall, low spatial and spatial factors play an important role in the changes of precipitation. In November, while strengthening the system of precipitation in the region, the role of spatial factors in changes to rainfall reaches its peak in December, but due to the power systems of the proper moisture and nourishing rainfall, of the role of regional rainfall eased on location factors and changes in precipitation are more associated with atmospheric agents.

Successful management of groundwater resources using numerical models requires knowledge of spatial distribution of hydraulic heads and it's fluctuation, aquifer parameters and other input data. this paper's aim is application and evaluation of geostatistcal model for optimal estimation of Groundwater Table Level in an area of 999 sq km in part of the north west of Kermanshah plain. To achieving this, we used the data of Water table elevations in the 50 monitoring wells in studding area. Firstly we analyses the spatial correlation of monitoring wells With the use of measured elevations of the water table, experimental semivariograms were constructed that characterizes the spatial variability of the measured groundwater levels. Linear, Spherical, Exponential and Gaussian semivariogram models were fitted to the experimental semivariogram. The finally selected models were used to estimate the groundwater levels and estimation variance (which express the best accuracy of the estimated groundwater levels). Then 3 geostatistcal interpolation method (ordinary, sample and universal Kriging) applied to interpolate water table elevations from their measurements at random locations. The cross validation algorithm was used to estimation then 7 statistical indexes (RMSE, RMESu, RMSEs, MAE, MBE, d, R2) apply to evaluation and comparing 3 mentioned interpolation method. The results indicated that the ordinary kriging(OK) with exponential semivariogram and by including 8 neighbor were the best method for modeling and interpolating ground water table level in studding area.the out pout of this paper can be applied to optimization the locate of wells network. The water resource planner and decision maker in this field can apply this optimum interpolated water table to monitoring the spatiotemporal fluctuation of water table in this area by updating it's data.

Groundwater is the main water resource for agricultural demands in arid and semiarid regions. An Sustainable agriculture requires a precise management and scheduling on utilizing these resources which in turn needs adequate knowledge about spatial variability of groundwater level for a given time period. As traditional interpolation methods do not consider spatial correlation between groundwater level observations, geostatistical methods are used for spatial variability analysis and mapping of groundwater level. In this study first a semivariogram is used to investigate the spatial correlation of groundwater level data from 59 observation wells in Kuhpayeh-Sagzi aquifer (Esfahan Province). Semivariogram analysis was performed for groundwater level data from 2002 to 2009 and for wet (Ordibehesht) and dry (Mehr) seasons. Also Kriging is used to interpolate groundwater level data over the study area and the results are compared with those achieved by inverse distance weighing method. Geostatistical analysis is performed using GS+. Based on results obtained in this study, the best semivariogram model for groundwater level for all time periods was spherical. Moreover the ratio of nugget effect (C0) to Sill showed that groundwater level data are strongly correlated over space for all years and for both wet and dry seasons. The smallest range of influence (36850 m) was found for wet season in 2002-2003 and the largest range of influence (40220 m) was found for dry season in 2007-2008. The cross-validation results showed the better performance of ordinary Kriging in comparison to inverse distance weighting. Based on the generated maps, the lowest groundwater level was seen in southeast and highest groundwater level was seen in center, south and southwest of the study area.

Inflation of population and rising living standards in many countries need to be enhanced the high quality water suitable for different uses such as agricultural، industrial and drinking sections. Groundwater is one of the most important water supply sources which are encountered with many problems such as drawdown، recharge reduction due to low rainfall and different natural and man-made pollutions. Therefore، monitoring of groundwater quality is very important. Chemical hazards are one of the major environmental hazards in the field of water quality issues and other areas that jeopardizes the health and security of human. Researchers report results from the application of geostatistics in hydro-solving processes، increase accuracy، and reduce the number of samples collected from the economic point of view. Study Zehtabian et al. (2010:61) with the aim of modeling spatial variation of groundwater quality using geostatistical methods، showed that Co-Kriging method is more accurate than radial basis function and the inverse distance weighting methods. Maghami et al. (2011:171) for groundwater quality zoning in Abadeh city used kriging and inverse distance weighted. Comparing the results of this study showed that kriging method with semi variogram of circle is compared to other methods. Spatial prediction of fluoride concentration in groundwater resources in the North West of Iran indicated that Kriging method with r= 0. 73 was less than Co-kriging (r= 0. 86) (Asghari Moghaddam et al.، 2008:1). Survey data and the findings indicate human use of chemical fertilizers and reduce the quality of water resources. Such a situation is not only caused environmental sustainability، sustainable development، but also to the environment will be broken. Therefore، unsustainable human development، along with its non-application of chemical fertilizers is one of the most important environmental hazards at all levels of society. The purpose of this study was the spatial variability modeling of water quality parameters in Hamedan - Bahar plain by geostatistical methods. Study Area: Hamadan – Bahar plain، called Siminehrood، with an area of 2459 km2 along 48° 17'' to 48° 33 E and 34°49'' to 35°02'' N is located in the northern highlands of Alvand. For zoning of aquifer parameters used data of 25 observation wells during the spring and summer in during 2009-2010 years (Fig. 1). Fig. 1 Location of the study area Lack of adequate surface water، rainfall and rainfall duration mismatch causes excessive pressure on groundwater resources for supplies more than 80 percent of agricultural water and 50 percent of drinking water aquifer is above (Balali et al.، 2010:194). On the other hand، indiscriminate and inappropriate use of fertilizers to increase agricultural production can alter the quality of groundwater resources. For zoning of the aquifer quality، the data of 25 observation wells during the spring and summer of the years 2009 and 2010 were used. As the season of spring probe picked up in order to perform the irrigation of crops، and the importance of summer as the season of low water، picked up، and the spring is to provide drinking water for the cities of Hamedan. The parameters studied were EC، pH، SAR and TDS as the main characteristics of groundwater. For interpolation of data in locations without measurements، were used three methods of geostatistical including ordinary kriging (OK)، inverse distance weighting (IDW) and radial basis function networks (RBF). For choice modeling method، Normal Root Mean Square Error (NRMSE) and Mean Bias Error (MBE) in the form of cross-validation technique was used. The results showed that kriging with spherical semi-variogram are useful for modeling qualitative factors (Fig. 2). NRMSE of the spherical semi-variogram for each of the four parameters was 0. 95 to 0. 96 that was lower to other semi-variogram (0. 96-0. 98). The lowest error was modeled on the parameters pH، and the maximum error was awarded to EC parameters with NRMSE=0. 42 and MBE= -0. 01. Fig. 2 The semi-variogram of each of the quality parameters Accordingly، the zoning was done for the interpolation of aquifer quality parameters based on the information of plain aquifer. The map of zoning showed that trends of EC and TDS are similar. One of the main reasons of similarity changes is because of a linear relationship between these parameters. The results of zoning indicated EC، TDS and SAR values has increased form the South East along the North East. So that SAR from 1. 9-28 to 1. 2-0. 8، EC from 2395. 3-1266. 4 to 823. 5-483. 3 µmoh/cm and TDS from 1591. 3-826. 3 to 526. 2-295. 7 mg/L decreased (Fig. 3). But change of pH was non-uniform than the other three parameters and its maximum was in the north-west plains (7. 75-7. 93). Also، The accuracy of geostatistical methods in the estimation of the area under study (non-peak) was higher. The reason is due to lack of measurement points in border studies، and regional climatic factors in causing maximum points، which is not in the geostatistical methods. The results showed that kriging with spherical semi-variogram are useful for modeling qualitative factors. Also، the results show that the statistical accuracy is low in estimation of water quality parameters at maximum points. In general it can be stated، with water quality values at one point، can estimate amount to the same quantity at a point with known coordinates and high precision.