Showing 15 results for Variability
Jahangard Mohammadi,
Volume 2, Issue 4 (1-1999)
Abstract
This study addresses the methodology of studying spatial variability of soil salinity. The information used is based on a semi-detailed soil survey, followed by a free survey, conducted in Ramhormoz, Khuzestan. The study of soil salinity variations was carried out using about 600 sampling points with an average distance of 500 m, at three depths of 0-50, 50-100, and 100-150 cm. To determine the spatial variability of soil salinity at different depths, the variogram which is a statistical function for the spatial variability analysis of the geographical variables was used. The results indicate that all variograms show almost the same range of 12 - 13 km which is closely related to the geographical distribution of the soil parent materials in the area. Ordinary block kriging was used to map salinity at different depths for a block dimension of 500 × 500 m. A comparison between the kriged estimates and the soil salinity map, produced during the soil survey, showed that the overall similarity between the test data and the classified kriging estimates was 40%, while the overall agreement between the test data and the soil survey salinity map was 36%. A detailed similarity calculation showed that the reliability of the classified kriging estimates representing the lowest salinity classes (S0, S1) is larger (75%) than the reliability of the soil survey salinity map representing these classes (50%). Consequently, the results indicate that geostatistical tools can be used to support the present-day procedures of soil salinity mapping.
J. Mohammadi, H. Khademi, M. Nael,
Volume 9, Issue 3 (10-2005)
Abstract
In order to achieve a sustainable management of land resources and to improve land quality, quantitative assessment of effective factors and soil quality indicators are required. The aim of this study was to evaluate variability of selected soil quality attributes in central Zagros affected by such factors as region, land use and management practices. Twelve sites were selected in three provinces including Chahar Mahal va Backtiari (Sabzku, Broujen), Isfahan (Semirum), and Kohkeloyeh va Boyerahmad (Yasodje). Different management practices were considered such as: protected pasture, intensive grazing, controlled grazing, dryland farming, irrigated wheat cultivation, legume-farming practice, protected forest, and degraded forest. Systematic sampling with taking 50 samples of surface soil in each site was carried out. The results of univariate and multivariate analysis revealed that all factors significantly influenced the spatial variability of selected soil quality attributes namely phosphatase activity, microbial respiration, soil organic matter, and total nitrogen. The results obtained from discriminant analysis indicated that all selected soil quality parameters could significantly be used as soil quality indicators in order to recognize and discriminate sustainable agricultural and forestry ecosystems and/or optimal management practices.
S. Mohammad Zamani, Sh. Ayoubi, F. Khormali,
Volume 11, Issue 40 (7-2007)
Abstract
Evaluating agricultural land management practices requires a thorough knowledge of soil spatial variability and understanding their relationships. This study was conducted at a traditionally operated wheat field in Sorkhankalateh district, located about 25 km northeast of Gorgan, in Golestan province, Iran. Soil samples of the 0-30 cm depth were collected right after planting at the end of autumn 2004 , 100 × 180m plot in a nested grid pattern (n=101). A 1 m2 plot of wheat was harvested at each of 101 sites previously sampled at the end of spring. Statistical results showed that frequency distribution of all data was normal. The highest and lowest CV was related to grain yield (20.40%) and pH (0.59%) respectively. Variogram analysis showed that all parameters had spatial structure and the range values showed considerable variability among the measured parameters. The ranges of spatial dependence showed a variation from 23.99m for total N up to 93.92m for K. Among the parameters, total N and ESP had stronger spatial dependence while P had the lower spatial dependence. Interpolated maps of Kriging demonstrated that crop and soil properties did not have a random pattern but had a spatial distribution. The spatial distribution of total N was similar to organic matter and also there was similarity between spatial distribution of harvest index and available P. The results demonstrated that, the spatial distribution and spatial dependence level of soil properties can be different even within similarly managed farms. Variography and Kriging can be useful tools for designing soil sampling strategies, characterizing management zones and variable application rates of inputs in the precision agriculture.
H. Sabouri, A.m. Rezai, A. Moumeni,
Volume 12, Issue 45 (10-2008)
Abstract
In order to study the genetic diversity of 75 Iranian rice genotypes (45 Iranian land race, 25 improved cultivars, and 5 exotic cultivars) with respect to their salinity tolerance at seedling stage and to determine tolerance indices, based on biomass, genotypic code and Na+/K+ ratio a factorial experiment in randomized complete block design with three replications was conducted under control and salt stress(1.2, 4 and 8 dSm-1) conditions at Rasht Rice Research Institute. Root and shoot length, root and shoot dry weight, Na+ and K+ concentrations, and genetic score were studied. Significant differences were detected among genotypes for all traits. Shoot length and K+ concentration had the highest and lowest heritability estimates, respectively. Genetic score under salinity stress showed that Tarom-mahalli, Gharib, Shahpasand Mazandaran and Ahlami-Tarom with more biological yield root and shoot lenghes, and low Na+/K+ ratio were tolerant. Khazar, Speedroud, IR28 and IR29 were the most sensitive cultivars. Tarommahalli, Ahlamitarom, Rashti and Chparsar had low tolerance index, mean productivity, stress sensitive index, geometric mean index, stress tolerance index and harmonic mean for genetic score, whereas Khazar and Speedroud had high values for theses indices. Cluster analysis, based on seedling traits at 4 and 8 dS.m-1 divided the genotypes to three groups. Tolerante group had low genetic score and Na+/K+ ratio, but high root and shoot dry weight, biomass, root and shoot length.
Sh Ayoubi, F Khormali,
Volume 12, Issue 46 (1-2009)
Abstract
Understanding distribution of soil properties at the field scale is important for improving agricultural management practices and for assessing the effects of agriculture on environmental quality. Spatial variability within soil occurs naturally due to pedogenic factors as well as land use and management strategies. The variability of soil properties within fields is often described by classical statistical and geostatistical methods. This research was conducted to study what factors control the spatial variability of soil nutrients using an integration of principal component analysis and geostatistics in Appaipally Village, Andra Pradesh, India. 110 soil samples were randomly collected from 0-30 cm and prepared for laboratory analyses. Total N, available P, Ca, K, Na, Mg, S, B, Mn, Fe, Zn were measured using standard methods. Statistical and geostatistical analysis were then performed on raw data. The results of PCA analysis showed that 4 PC's had Eigen-value of more than 1 and explained 71.64 % of total variance. The results of geostatistical analysis revealed that three PC's had isotropic distribution based on surface variogram. Spherical model was fitted to all PC's. Ranges of model were 288 and 393 m for PC1 and PC3 respectively. On the other hand the range for PC2 was significantly different (877m). The most important elements in PC2 such as Fe, Mn, and Zn probably had similar range of effectiveness (700-900m). The comparison of PC's distributions indicated that PC1 and PC3 including total N, available Mg, K, Cu, Ca and P, were in accordance with farming plots dimensions and management practices. Therefore, it is necessary to improve the appropriate fertilizers used by farmers. The pattern of PC2 distribution was not consistent with farmer's plots, but had the best concordance with soil acidity. Therefore, the most correlated elements with this PC including Fe, Mn, and Zn are mainly controlled by soil acidity and not affected by management practices. However, spatial variability of these elements in areas lower than critical values should be considered for site-specific management.
S Sadr, M Afyuni, N Fathian Por,
Volume 13, Issue 50 (1-2010)
Abstract
Industrial, agricultural and urban activities have contaminated soil by heavy metals that can also increase concentration of the metals in food chains. This study was carried out in Isfahan province where lots of such activities are in progress. The purpose of this study was to determine spatial variability of Arsenic )As) in Isfahan soils. In this research, the soil samples )0-20 cm) were collected in a stratified random sampling system at about 4 Km intervals in a study area of 6800 Km2. The positions of samples were recorded using a GPS. After laboratory preparation, soil samples were measured for total As. Spatial structures of total As were determined by directional variograms. Spherical model was the best model to describe spatial variability of As. Mean-square error )MSE) and correlation coefficient were used to validate variograms. Distribution map for Arsenic was prepared using the obtained information from element by point kriging method and by using Surfer software. Interpolation in blocks by dimensions of 1000×1000 m was made. The mine effective factors with high concentration of As are parent material, and direction of dominant wind has affected the spread of As in north-west of the study area.
Y. Safari, I. Esfandiarpour Boroujeni,
Volume 17, Issue 65 (12-2013)
Abstract
In order to study the precision of qualitative land suitability classification method for main irrigated crops (i.e. potato, sugar beet, wheat and alfalfa) in the Shahrekord plain, qualitative land suitability maps were obtained for all the studied crops according to representative pedon analysis using simple limitation method. In the next step, a regular grid sampling consisting of 100 sample points with a distance of 375 m was designed. Then all required analyses were done to recognize the suitability class of these sites for each land use. Finally, land suitability results for all the observation points in each map unit were compared with the results of its representative pedon. The results showed the average of measured compatibility between representative pedon and other observation points in each map unit in class and subclass levels was about 60 % and 38 %, respectively. Due to the generalization of representative pedon analyses to all unit area, the use of soil map units as land suitability units may lead to unsatisfactory results. Therefore, the use of representative pedon is not recommended in sustainable land management and precision agriculture. However, new techniques like geostatistics can be used to improve the conventional soil mapping methods.
M. Mosalaei, H. Shirani, V. Mozafari, I. Esfandiarpour,
Volume 18, Issue 70 (3-2015)
Abstract
Salinity and ions toxicity are one of the main problems of agricultural lands in arid and semi-arid regions, such as Iran. In addition to the salinity problem, some other marks like boron toxicity in crops have been seen in Hossein Abad area as one of the main agricultural regions of Yazd. Therefore, this study intends to evaluate and analyze spatial variability of soil salinity as an aspect of soil degradation, and prepares soil salinity and boron maps. A regular grid sampling scheme was done through a 150 m interval. Salinity and boron were measured at the depth of 0 to 30 cm. Totally 104 samples were measured. After statistical analysis of the data and studying their distribution, Kriging estimator was used for mapping the mentioned variables. Results showed that the region has a salinity problem and does not have any boron toxicity. According to the relationship of nugget effect and sill, there was a strong dependency among all the measured factors except for boron and pH factors. The least salinity was observed in cultivated areas due to the leaching process. The boron range was between 0.07 and 1.6 mg kg-1. Salinity and soil boron were significantly correlated at 99 % confidence level. Based on the Spearman and Pearson tests, there was a positive correlation between SAR and salinity at 99 % confidence level, which shows the region has more sodic salts than others. Also, pH of the region did not present any problem for growing crops.
S. Norouzi, H. Khademi,
Volume 19, Issue 72 (8-2015)
Abstract
Spatial and temporal distribution of dust deposition rate (DDR) in Isfahan city and the influencing climatic parameters were studied. Dust samples were collected using glass trays placed on the roof of one-story buildings from 20 sites in Isfahan city for 12 months. Climatic data were obtained from Meteorological Organization and analyzed. The highest and the lowest amount of DDR in agreement with the direction of prevailing wind were observed for dry months with eastern and northeastern wind directions and wet periods with western and southwestern wind directions, respectively. This can indicate dust emission from the desert located in eastern part of Isfahan city. Statistically significant inverse correlation between DDR and precipitation and relative humidity, and significant and positive correlation of DDR with Min and Max temperatures in all the studied months and also with Max and average wind speed for dry sampling months may well justify the temporal distribution of DDR in the city. In dry months, finer particles from eastern desert can be transported a longer distance and deposited in the western part of the city, far from the source area. In wet seasons, however, soil aggregates become coarser as a result of particle adhesion. This, in turn, results in the deposition of dust near the source area as the transporting power of dust reduces.
M. Ayoubi, R. Sokouti, M. J. Malakouti,
Volume 20, Issue 76 (8-2016)
Abstract
This study is aimed to investigate the spatial variation of soil macronutrients such as phosphorus, potassium and organic matter using different methods of Geostatistics and Geostatistical method combined with Fuzzy logic to estimate the values of this element to provide a spatial distribution map for the proper distribution of fertilizer in the plain of Uremia. Spatial variations in soil nutrients are natural but knowing these changes for careful planning and management particularly in the agricultural lands is simply inevitable. This information is necessary to increase the profitability and sustainable agricultural management. Therefore, to estimate the changes in the elements of places not sampled, the Kriging, Fuzzy Kriging, Cokriging and Inverse Distance Weighting methods have been used in GS +. In this study, Matlab 9.1 software was used to fuzzification of the data and GIS was used for the final mapping. The parameters MAE, MBE and RMSE were used to compare these methods. The results showed that the combined method of Fuzzy Geostatistic with the mean absolute error values for the elements phosphorus, potassium and organic matter i.e. 0.17, 0.18 and 0.18, respectively, is recognized as the preferred method based on which zoning maps have been prepared for P, K and OC in GIS.
Z. Savari, S. Hojati, R. Taghizadeh-Mehrjerdi,
Volume 20, Issue 77 (11-2016)
Abstract
Salinity and alkalinity decreases physical, chemical and biological quality of soils and as a result reduces crop yield. This study aims to evaluate spatial variability of soil salinity in Ahvaz using geostatistical approaches. Accordingly, 69 surface soil samples (0-10 cm) were collected and their electrical conductivities (EC) were measured in 1:1 soil: water extracts. The data were then analyzed using ordinary kriging (OK), log-normal kriging (LOK) and indicator kriging (IK) interpolation techniques to produce soil salinity maps. Finally, the quality control of soil maps was performed by calculation of root mean square error (RMSE) and coefficient of determination (R2). The results indicated that due to the lowest RMSE and the highest R2 values, the LOK interpolation method is the best approach in mapping soil salinity in Ahvaz. The results also illustrated that based on defined threshold values (4, 8, 16, and 32 dS m-1) the indicator kriging methods have been able to show risk of soil salinity in the area. Based on this, most of the area is covered by soils with salinity higher than 4 dS m-1. Evaluation of final soil maps showed that the highest concentrations of salts are related to the western and southwestern parts of Ahvaz city. In contrast, the lowest amounts of salinity were found in Eastern and Northern parts of the city.
F. Moosiri, N. Ganji Khorramdel, M. Moghaddasi,
Volume 22, Issue 1 (6-2018)
Abstract
To continue or develop the exploitation of underground water for different different uses and purposes, as well as building any water structure, set of quantitative features of aquifers can be detected. To achieve this goal, quantitative monitoring of groundwater level is only possible. Accordingly, this study compared the impact of both the concept of marginal entropy and ordinary kriging for groundwater level monitoring network design in the case Gotvand-Aghili Plain, Khuzestan province. It is important to note that a key aspect in groundwater level monitoring of the quantity measured was the variability or uncertainty in it. This created a considerable confidence to monitor and ultimately achieve favorable conditions in the future. In this study, the variability of the groundwater level was considered to evaluate the combined effects of marginal entropy and ordinary kriging. In order to determine the suitable areas for further monitoring or thinning as well as the compatibility of these two methods, the monitor network design was designed. The map classified according to the marginal entropy method, in a range between 0.07 to 5.26 of the marginal entropy change, areas with the higher rates of 2.13 in terms of density; this indicated the need for more observation wells. Ordinary Kriging method also changed the range of values; they also represented areas that needed monitoring more than 13.16. Comparison of the results obtained by the two methods showed that the marginal entropy of the kriging method with less uncertainty and by using it, there was less the need to be monitored and classified. Comparison of the two methods by the zoning map showed that fewer errors were taken to the marginal entropy method and it could be recommended for the groundwater level monitoring network design. The network was also based on the Cross validation estimation error evaluated. These tests and additional analysis were employed in this study to determine the suitable areas for the higher density of wells and the need for thinning areas. The results further confirmed the proper performance of the methods employed, as well as the superiority of the marginal entropy in the design of a small groundwater monitoring network.
A. Karami, M. Homaee,
Volume 22, Issue 4 (3-2019)
Abstract
Quantitative description of the spatial variability of soil hydraulic characteristics is crucial for planning, management and the optimum application. Field measurement of infiltration is very expensive, time-consuming and laborious. Soil structure also important effects on water infiltration in the soil. The objectives of this study were to determine the spatial variability of water infiltration, to select the most appropriate infiltration model, to calculate the parameters of relevant models, and to quantify the soil structure by using the fractal geometry. Infiltration parameters were estimated by using some physical soil properties, as well as fractal parameters, in this research. To achieve these purposes, 161 sites were selected and their infiltration was measured by using the constant head double-ring infiltrometers method in a systematic array of 500*500 m. The observed infiltration data from all examined sites were fitted to three selected infiltration models. Soil bulk density (BD), soil water content, soil particle size distribution, soil aggregate size distribution (ASD), organic carbon content (OC), saturation percentage (SP), soil pH and electrical conductivity (EC) were also measured in all 161 sites. For the quantitative assessment of soil structure, the aggregate size distribution, fractal parameters of the Rieu and Sposito model as well as the mean weight diameters (MWD) and geometric mean diameter (GMD) were also obtained. The obtained results indicated that the infiltration rates of the studied areas had generally low basic infiltration rates (1.1-31.1 cm hr-1) for most sites with the average of 6.69 cm hr-1. According to all obtained results and based on the least-square method, the Philip model was selected as the best performing model to account for infiltration. The aggregate size distribution demonstrated a fractal behavior, and the infiltration parameters could be significantly correlated with the fractal parameters and other soil physical properties.
H. R. Matinfar, Z. Mghsodi, S. R. Mossavi, M. Jalali,
Volume 24, Issue 4 (2-2021)
Abstract
Knowledge about the spatial distribution of soil organic carbon (SOC) is one of the practical tools in determining sustainable land management strategies. During the last two decades, the utilization of data mining approaches in spatial modeling of SOC using machine learning algorithms have been widely taken into consideration. The essential step in applying these methods is to determine the environmental predictors of SOC optimally. This research was carried out for modeling and digital mapping of surface SOC aided by soil properties ie., silt, clay, sand, calcium carbonate equivalent percentage, mean weight diameter (MWD) of aggregate, and pH by machine learning methods. In order to evaluate the accuracy of random forest (RF), cubist, partial least squares regression, multivariate linear regression, and ordinary kriging models for predicting surface SOC in 141 selected samples from 0-30 cm in 680 hectares of agricultural land in Khorramabad plain. The sensitivity analysis showed that silt (%), calcium carbonate equivalent, and MWD are the most important driving factors on spatial variability of SOC, respectively. Also, the comparison of different SOC prediction models, demonstrated that the RF model with a coefficient of determination (R2) and root mean square error (RMSE) of 0.75 and 0.25%, respectively, had the best performance rather than other models in the study area. Generally, nonlinear models rather than linear ones showed higher accuracy in modeling the spatial variability of SOC.
H. Nazaripour, M. Hamidianpour, M. Khosravi, M. Vazirimehr,
Volume 26, Issue 4 (3-2023)
Abstract
In this study, the decade variability of frequency and severity of drought in Iran has been investigated. The one-month scale data from the standardized precipitation-evapotranspiration index (SPEI 01) in the period 1956 - 2015 have been used. Based on the common numerical thresholds, the characteristics of the frequency and severity of drought for each pixel have been calculated and they are the basis for the analysis of the drought situation. Then, the frequency of drought severity classes was calculated and its trend was investigated using the non-parametric Mann-Kendall test. The findings indicated the spatio-temporal variability of drought frequency and intensity patterns in Iran. The frequency of mild droughts has decreased from south to north and from east to west; while the frequency of more severe droughts has increased from north to south and from west to east. The frequency of mild droughts in the southeast, northwest, and northeast has increased by 5 to 40 percent. While the frequency of more severe droughts in most parts of Iran has increased between 10 and 20 percent. Variability in the frequency of more severe droughts is more pronounced in the Central Plateau catchment area as well as in the Persian Gulf-Oman Sea. The trend of drought intensity is decreasing (drought intensification) at the same time as the prevailing rainfall regime in Iran. A significant increase in drought intensity (wet season intensification) is observed only in southeastern Iran at the same time as the monsoon regime. However, extra-arid and arid regions of southeastern Iran are affected by the frequency and severity of drought and have a high degree of vulnerability.
