K. Kamali; Gh. Zehtabian; tayybe Mesbahzadeh; M. Arabkhedri; Hossain Shohab Arkhazloo; A. Moghadamnia
Abstract
Introduction: Soil quality is an essential indicator for sustainable land management that generally depends on soil physical, chemical and biological properties. Due to the multiplicity of soil properties, the number of variables is usually reduced to a minimum set by statistical methods, which reduces ...
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Introduction: Soil quality is an essential indicator for sustainable land management that generally depends on soil physical, chemical and biological properties. Due to the multiplicity of soil properties, the number of variables is usually reduced to a minimum set by statistical methods, which reduces study time, decreases monitoring cost for sustainable use of agricultural lands. The aim of this study was to introduce the most effective soil characteristics of agricultural lands in Mohammadshahr plain, Karaj, to prevent the descending trend of soil quality.
Materials and Methods: In this study, four farms and orchards which were different in terms of crop type and irrigation system were selected and evaluated with Integrated Quality Index (IQI) and Nemero Quality Index (NQI). In both indicators, the characteristics affecting soil quality are combined in the form of a mathematical model and presented as a numerical quantity. For this purpose, first 12 soil profiles were described, followed by sampling from topsoil (surface layer) and sublayers (weighting average for the depths) and testing 17 soil characteristics affecting its quality. In the next step, both indicators were calculated using two different sets of soil properties. The first category, the Total Data Set (TDS), included all measured soil characteristics, and the second group, the Minimum Data Set (MDS), included the most important properties affecting soil quality. The Principle Component Analysis was implemented to select the MDS. Soil properties were scored to calculate IQI and NQI. For this purpose, a function was defined for each soil feature to standardize all scores between zero and one. Weighting various soil quality properties was also performed by calculating the common variance of the variables, which was obtained by factor analysis method.
Results and Discussion: Calculation of IQI and NQI indices showed that the topsoil samples were in grade III and sublayer samples belonged to grade IV with major limitations due to lack of profile development, organic carbon deficiency, salinity and high gravel. Four and six items out of 16 variables were identified effective for topsoil and sublayers, respectively. The IQI index based on TDS was more accurate and sensitive than the NQI index for soil quality assessment, as more features are considered for TDS. In the IQI index, both the weight of attributes and their scores are effective, while in the NQI index, only the attribute score is considered. On the other hand, the coefficient of determination between the TDS and MDS for topsoil and sublayer samples was 0.55 and 0.56% for IQI model, respectively, and 0.48 and 0.16% for NQI model, respectively. In other words, the determination coefficients showed the reliability of using the MDS instead of TDS in both IQI and NQI models. In the MDS, mean weight diameter (MWD) showed the highest effect on the surface layer and percentage of gravel had the greatest impact on the soil quality of the sublayer.
Conclusion: Although TDS took into account all soil properties and showed a slightly higher coefficient of determinations with both soil quality indicators, the MDS obtained similar results to the TDS with only about half of the properties. In the MDS, the features with an internal correlation is eliminated rendering it more cost effective. The results of this study assist decision-makers to choose better quality management and soil sustainability strategies while decreasing the monitoring cost.
Hossain Shohab Arkhazloo; H. Emami; Gholam Hosain Haghnian; Abazar Esmali
Abstract
Introduction: Gully erosion is an important type of soil erosion in Iran and Ardebil province (Moghimi and Salami, 2011; Khatibi, 2006). Increasing the cross section of gullies is an indicator for gully developing (Deng et al, 2015). Topography and soil properties are two important factors in gully developing ...
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Introduction: Gully erosion is an important type of soil erosion in Iran and Ardebil province (Moghimi and Salami, 2011; Khatibi, 2006). Increasing the cross section of gullies is an indicator for gully developing (Deng et al, 2015). Topography and soil properties are two important factors in gully developing in various regions of worldwide (Poesena et al, 2003). Despite the importance of soil properties in gully erosion, the direct effect of these agents was less investigated and few researches have been carried out to the effect of physical and mechanical soil properties on gully erosion. Therefore, the objectives of this research were to determine 1) the effect of topography on gully erosion, 2) effect of surface and subsurface soil physical and mechanical properties on increasing the cross section of gullies and 3) to select the most important soil properties affect developing the cross section of gullies in three regions of Ardebil province (Ortadagh, Molla Ahmad, and Sarcham). In addition, the relationship between the most soil properties and topographic agents was investigated
Materials and Methods: The effect of topography on gully erosion was investigated by using of two methods i.e. topographic threshold of gully forming (as , where A and S is gully watershed cross section and slop, respectively, a and b is local coefficients) and the relationship between slope classes with gullies density. In regard to catchment characteristics, a set of similar gullies was selected in each region and the changes of cross section area for gullies in four points along its length were measured as indicator of gully development during two years. 17 physical and mechanical of surface and subsurface soil properties in each point were measured and the most important properties that affect on gully development were selected based on principle component analysis (PCA) method. Finally, the stepwise regression model was fitted to the soil properties selecting from PCA for gully's development in each region.
Results: The relationship between Slope classes and gully density showed that in MollaAhmad region gully density was increased with increasing the slope. In OrtaDaghregion, similar trend was observed up to 20-30% slope, while in Sarcham region these was no relationship between slope classes and gully density. According to the topographic threshold it seems that runoff is the main agent for gully forming in MollaAhmad,but in Sarchamthe piping and tunnel erosion might have caused gully formation and in Ortadagh both surface and subsurface flows were recognized as effective agents for gully formation. Increasing values of the cross section for the selected gullies during 2 years was 0.9, 0.6, and 0.8 m2 for Ortadagh, MollaAhmad, and Sarcham regions respectively, which were 41, 44 and 61 percent more than their initial cross sections. Among mechanical soil properties, liquid limit (LL), plastic limit (PL) and shear strength (SS) had the negative and significant correlations with increasing the cross sections of gullies in 3 regions. Among the particle size fractions, Water dispersible clay had the most effect on increasing the gully’s cross sections and except for surface depth of Molla Ahmad, its correlation with gully’s cross section was significant. Principle component analysis (PCA) demonstarated that in MollaAhmad and Ortadagh mainly mechanical properties of soil and aggregate stability had the more effect on increasing the gully cross section, but in Sarcham soil particle size classes and aggregate stability indices had more effect on gully’s cross section.
Conclusion: According to topography threshold, it can be concluded that surface runoff is the main agent for gully forming in MollaAhmad and gully density increases by increasing the slope classes. In this region the effect of surface runoff on surface soil erosion was sever. In Sarcham there was no relationship between slope and gully density and it was found that the subsurface flow is predominant factor for gully forming. In OrtaDagh both surface and subsurface flows were the main factors for gully forming, so due to increasing the surface flow up to slope 20-30% class, maximum gully density was noted in this slope class and the effect of subsurface soil properties in developing gully cross section was higher than surface soil properties. In general, the relationship between gully density with slope classes, topographic threshold and soil physical and mechanical properties which were effective on gully development indicated the close consistency between the type of hydrologic flow in gully forming and the most important soil properties on increasing the gully’s cross section.
H. Shohab Arkhazloo; H. Emami; Gh. Haghnia; A.R. Karimi
Abstract
Abstract
Soil quality evaluation is an essential issue in soil management for agriculture and natural resource protection. Soil quality indices are useful tools for determination and comparison of soils quality. Using of principle component analysis in this study we selected 6 important properties as ...
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Abstract
Soil quality evaluation is an essential issue in soil management for agriculture and natural resource protection. Soil quality indices are useful tools for determination and comparison of soils quality. Using of principle component analysis in this study we selected 6 important properties as a soil quality minimum data set (MDS) among 18 soil properties (TDS). Then, soil quality of agriculture and pasture lands in DehSorkh region in south of Mashhad city was evaluated by Integrated quality index (IQI) and Nemero quality index (NQI) in two collections of soil properties include MDS and TDS. The results showed that soils of the region had low quality in respect to studied indices and was significant correlation between IQITDS - IQIMDS and between NQITDS - NQIMDS. Generally those results show that determined MDS can be a suitable representative of TDS. In addition, comparison of soil quality indices between agriculture and pasture soils showed that efficiency of TDS collection in determining land use effect on soil quality indices was better than that of MDS.
Keywords: Integrated quality index, Nemero quality index, Principle component analysis
H. Shohab Arkhazloo; H. Emami; Gh. Haghnia; A.R. Karimi
Abstract
Abstract
Soil quality is an essential concept for maximum agriculture production without environmental destruction. Studying soil physical quality indicators, that express soil structural stability and soil air-water balance in root zone, is one of the most important aspects of soil quality. So determination ...
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Abstract
Soil quality is an essential concept for maximum agriculture production without environmental destruction. Studying soil physical quality indicators, that express soil structural stability and soil air-water balance in root zone, is one of the most important aspects of soil quality. So determination of optimal range for pore volume distribution is important and this research carried out to determine i) the optimal range for pore volume distribution according to soil physical quality indicators ii) the effect of soil properties on the slope of retention curve at its inflection point or Sgi index and iii) the effect of type of land use on soil physical quality indicators. The classification of studied soils was Haplocalcid, soil texture varied from sand to clay loam and organic carbon (OC) also changed between 0.2 to 2.2 percentages. In this study, Sgi index and pore volume distribution were determined by fitting the experimental soil retention curve data of 40 soil samples to van Genuchten equation in agricultural and rangeland land uses in south of Mashhad plain. Also some other soil physical quality indicators such as, percentage of organic carbon, bilk density, sodium absorption ratio (SAR), mean weight diameter of wet aggregates (MWD), relative field capacity (RFC), plant available water capacity (PAWC), air capacity (AC), and structural stability index (SI) were measured. Then the optimal range of pore volume distribution was determined by using of 8 soil physical quality indicators. Also the correlation between Sgi index and soil physical properties was determined. The positive and significant correlation between Sgi index and percentage of %OC, mean MWD, RFC, and PAWC was shown. But there was a negative and significant correlation between Sgi index and SAR in both land uses. In addition, mean comparison of indicators in two land uses showed that, among the 8 indicators, Sgi index, MWD, PAWC has been decreased significantly in agriculture land use samples.
Keywords: Pore volume distribution, Sgi Index, Soil physical quality
