Sheyda Kaboodi; farzin shahbazi; Nasser Aliasgharzad; nosratola najafi; naser davatgar
Abstract
Introduction: Understanding soil biology and ecology is increasingly important for renewing and sustainability of ecosystems. In all ecosystems, soil microbes play an important role in organic matter turnover, nutrient cycling and availability of nutrients for plants. Different scenarios of land use ...
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Introduction: Understanding soil biology and ecology is increasingly important for renewing and sustainability of ecosystems. In all ecosystems, soil microbes play an important role in organic matter turnover, nutrient cycling and availability of nutrients for plants. Different scenarios of land use may affect soil biological properties. Advanced information technologies in modern software tools such as spatial geostatistics and geographical information system (GIS) enable the integration of large and complex databases, models, tools and techniques, and are proposed to improve the process of soil quality and sustainability. Spatial distribution of chemical and biological properties under three scenarios of land use was assessed.
Materials and Methods: This study was carried out in Mirabad area located in the western part of Souldoz plain surrounded by Urmieh, Miandoab, Piranshahr and Naghadeh cities in the west Azerbaijan province with latitude and longitude of 36°59′N and 45°18′E, respectively. The altitude varies from 1310 to 1345 with average of 1325 m above sea level. The monthly average temperature ranges from -1.4 °C in January to 24.6 °C in July and monthly precipitation ranges from 0.9 mm in July to 106.6 mm in March. Apple orchard, crop production field and rich pasture are three selected scenarios in this research work. Soil samples were systematically collected at 65 sampling points (0-30 cm) on mid July 2010. Soil chemical and biological properties i.e. microbial community, organic carbon and calcium carbonate equivalent were determined. The ArcGIS Geostatistical Analyst tool was applied for assessing and mapping the spatial variability of measured properties. The experimental design was randomized complete blocks design (RCBD) with five replications. Two widely applied methods i.e. Kriging and Inverse Distance Weighed (IDW) were employed for interpolation. According to the ratio of nugget variance to sill of the best variogram model three following spatial dependence conditions for the soil properties can be considered: (I) if this ratio is less than 25%, then the variable has strong spatial dependence; (II) if the ratio is between 25% and 75%, the variable has moderate spatial dependence; and (III) otherwise, the variable has weak spatial dependence. Data were also integrated with GIS for creating digital soil biological maps after testing analysis and interpolating the mentioned properties.
Results and Discussion: Spherical model was the best isotropic model fitted to variograms of all examined properties. The value of statistics (R2 and reduced sum of squares (RSS)) revealed that IDW method estimated calcium carbonate equivalent more reliably while organic carbon and microbial community was estimated more accurately by Kriging method. The minimum effective range (6110 m) was found for microbial community which had the strong spatial dependence [(Co/Co+C)
M. Rezaei; N. Davatgar; K. Tajdari; B. Abolpour
Abstract
Abstract
Guilan is a famous province in growing rice in Iran. Recently, due to shortage of water, farmers' desire to use groundwater in order to grow rice in northern part of Iran has been increasing rapidly. The fact that rice is sensitive to water quality, caused concern about rice cultivation sustainability ...
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Abstract
Guilan is a famous province in growing rice in Iran. Recently, due to shortage of water, farmers' desire to use groundwater in order to grow rice in northern part of Iran has been increasing rapidly. The fact that rice is sensitive to water quality, caused concern about rice cultivation sustainability in the area, especially in drought years. This study was done to investigate the spatial variability of some important ground water quality factors including EC, SAR and Na of samples taken from 135 wells over the region during the summer of 2007. First, the accuracy of Kriging (Ok) and Inverse Distance Weighting (IDW) with 3 different powers (1, 2 and 3) in mapping the studied parameters were evaluated. Then the final map was presented. The result showed that spherical model gave the best result to simulate the Vriograms. Although negligible difference was observed between the methods, Ok and IDW1 performed better in comparison to the IDW2 and IDW3. The final map showed that Ec in central part of the region, where the Sepidrod River meets the Caspian Sea is dramatically high which will threaten the sustainability of rice cultivation in the area. The other factors were in suitable level.
Keywords: Groundwater, quality, spatial variability, Iran
F. Meskini Vishkaii; M. Shabanpour; N. Davatgar
Abstract
Abstract
The saturated hydraulic conductivity (Ks) is an important physical property of soil. The direct measurement of this property in soils is a difficult and time consuming process. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil ...
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Abstract
The saturated hydraulic conductivity (Ks) is an important physical property of soil. The direct measurement of this property in soils is a difficult and time consuming process. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. The objective of this study is to determine effective factors on soil hydraulic conductivity using multiple-linear regression methods and to determine direct and indirect effects of input soil properties of model using path analysis method. 70 soil samples with medium to heavy texture were randomly collected from paddy fields in Guilan province after harvest of rice crop. Range of pH indicated acidic to neutral condition of paddy soils. Results showed that regression equation using geometric mean and standard deviation of soil particles diameter (dg and g), bulk density (b) and soil moisture at field capacity (0.033) as input variables, can estimate hydraulic conductivity with a good accuracy ( RMSE= 0.5 and R2adj=0.84). Although correlation between bulk density and saturated hydraulic conductivity was positive, but according to path analysis results, direct effect of bulk density on Ks is negative. Moreover the highest direct effect of soil properties on Ks in paddy soil was through soil water content at field capacity that indicates importance of this factor to predict saturated hydraulic conductivity.
Keywords: Pedotransfer functions, Geometric mean of soil particle diameter, Field capacity
