JWSS - Journal of Water and Soil Science

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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.

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Knowledge of the spatial dependency of soil properties, sensitive to grazing systems, is important from an ecosystem protection point of view. In the current study, geostatistical methods and fractal concepts have been used in order to characterize the impact of long-term grazing exclusion on the spatial variability of some soil chemical parameters including organic matter, total nitrogen, available phosphorous, and available potassium in both ungrazed and grazed sites located in Sabzkuh region, Chaharmahal Bakhtiari Province. The spatial pattern of different variables was studied using variogram. The results indicate that spatial variability of soil parameters depends upon grazing history. The variogram of organic matter in grazed areas shows a linear behavior without reaching the sill variance while organic matter in the ungrazed area established a strong spatial structure. Moreover, available phosphorous in the grazed area had pure nugget variation. Variograms of total nitrogen and available potassium in both grazed and ungrazed areas showed spatial structure approximated by spherical model. However, the range of variograms in exclusion sites was twice that of the grazed area. The results of applying the fractal theory show that soil properties have fractional behavior since increasing the scale of study reveals more details. Moreover, calculated fractal dimension values from variograms of different variables were close to 2.0 although this index was usually greater in the grazed area than in the exclusion sites. The calculated fractal dimensions can be used as a proper indicator of describing the pattern of spatial variability and its complexity.

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In this research, using geographic information system (GIS) and different geostatistical methods including the kriging and co-kriging (ordinary, simple and universal) as well as the radial basis functions, the spatial distributions of runoff coefficient were evaluated in Hamedan province. To this end, the annual runoff were calculated in 18 existing hydrometery stations and another 11 auxiliary points, using digital elevation model (DEM) and 11 years available data of the stations. The performance criteria for evaluating the methods were mean absolute error (MAE), mean bias error (MBE), root mean square error (RMSE), and general standard deviation (GSD) along with the cross validation examination. A high regression between the runoff coefficient and watershed average slope was selected as auxiliary variable. The results showed that the runoff coefficient of the region changes between 3.5 and 85%. The findings also indicated that the universal co-krigings with spherical semi-variogram model had better performance with the values of MBE (-0.0014), MAE (0.036), RMSE (0.054) and GSD (20.152). The universal and simple kriging with spherical model were equal in runoff estimation of the region and were ranked as the second methods to this propose.

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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.

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Groundwater is the most important source of water supply for agricultural purposes in arid and semi-arid areas. In many areas, excessive use of high quality water resources leads to reducing the available water resources and turning to the use of low quality water resources. Thus, knowing the temporal and spatial variation of groundwater quality is a necessary factor for implementation of sound water resource management and establishment of the suitability between water quality and its usage. In order to investigate water quality changes, this study was divided into two phases. In the first phase, for evaluation of the quality of groundwater for irrigation 76 wells were sampled in Bahadoran plain, in the year 2006. The SAR, EC, ions B3+ and Cl- were analyzed as the evaluation indexes. Then, using geostatistical methods the maps of each parameter were prepared. Finally, considering FAO criteria, these maps were overlaid and separate water quality maps were derived. The EC map indicated that in 48 and 52 percent of the groundwater lies in severe and slight to moderate restriction class for irrigation purposes. Moreover, the thematic map of infiltration restrictions indicates that the groundwater has no restriction in 66 percent of the area while 11% of groundwater causes low to moderate and 23 percent causes severe limitation. In the next phase, to examine changes in groundwater salinity during a 5-year period, 38 wells were sampled and the groundwater salinity map for the year 2011 was prepared. Finally, using subtraction of the salinity maps of given years, the salinity changes map was derived. The results of thematic map showed that groundwater salinity increased in 26.47 percent of the study area. In contrast, there was a decrease of about 31.14 percent in groundwater salinity over the 5-year period while 42.39 percent of the region’s groundwater remained unchanged. Since the study area is under cultivation of pistachios and salt threshold of this tree is 8 ds/m so the area of about 8 percent of the area was added to the previous limited areas. Therefore, irrigation management and planting development plan in Eastern and Southeastern areas should be revised.

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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.

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Determining the spatial distribution of different contaminants in soil is essential for the pollution assessment and risk control. Interpolation methods are widely used to estimate the concentrations of the heavy metals in the unstudied sites. In this study, the performances of interpolation methods (inverse distance weighting, local polynomials and ordinary Kriging and radial basis functions) were evaluated to estimate the topsoil contamination with copper and nickel in Golestan Province. 216 surface soil samples were collected from Golestan province, and their Cu and Ni concentrations were measured. Soil contamination was determined using different interpolation methods. Cross validation was applied to compare the methods and estimate their accuracy. The results showed that all the tested interpolation methods have an acceptable prediction accuracy of the mean content for soil heavy metals. RBF-IMQ and IDW1 methods had the lowest RMSE, whereas RBF-TPS method with the largest RMSE estimated a larger size for the polluted area. The greater the weighting power, the larger the polluted area estimated by IDW. Compared with the ‘‘sample ratio over the pollution limits” method, the polluted areas of Cu and Ni were reduced by 8.38% and 6.14%, respectively.

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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.

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