Determining the spatial distribution of soil properties using the environmental covariates and multivariate statistical analysis: a case study in semi-arid regions of Iran

Natural soil-forming factors such as landforms, parent materials or biota lead to high variability in soil properties. However, there is not enough research quantifying which environmental factor(s) can be the most relevant to predicting soil properties at the catchment scale in semi-arid areas. Thus, this research aims to investigate the ability of multivariate statistical analyses to distinguish which soil properties follow a clear spatial pattern conditioned by specific environmental characteristics in a semi-arid region of Iran. To achieve this goal, we digitized parent materials and landforms by recent orthophotography. Also, we extracted ten topographical attributes and five remote sensing variables from a digital elevation model(DEM) and the Landsat Enhanced Thematic Mapper(ETM), respectively. These factors were contrasted for 334 soil samples(depth of 0–30 cm). Cluster analysis and soil maps reveal that Cluster 1 comprises of limestones, massive limestones and mixed deposits of conglomerates with low soil organic carbon(SOC) and clay contents, and Cluster 2 is composed of soils that originated from quaternary and early quaternary parent materials such as terraces, alluvial fans, lake deposits, and marls or conglomerates that register the highest SOC content and the lowest sand and silt contents. Further, it is confirmed that soils with the highest SOC and clay contents are located in wetlands, lagoons, alluvial fans and piedmonts, while soils with the lowest SOC and clay contents are located in dissected alluvial fans, eroded hills, rock outcrops and steep hills. The results of principal component analysis using the remote sensing data and topographical attributes identify five main components, which explain 73.3% of the total variability of soil properties. Environmental factors such as hillslope morphology and all of the remote sensing variables can largely explain SOC variability, but no significant correlation is found for soil texture and calcium carbonate equivalent contents. Therefore, we conclude that SOC can be considered as the best-predicted soil property in semi-arid regions.

Weathering and soils formation on different parent materials in Golestan Province,Northern Iran

Geochemical, mineralogical, and micromorphologieal characteristics of soils and their relevant parent rocks including loess, ignimbrite, sandstone and limestone were investigated to identify the soil-parent material uniformity and the weathering degree of soils in Golestan Province, northern Iran. Highly developed Caleixerolls and moderately developed Haploxerepts were formed on loess and limestone, respectively. In contrast, the soils formed on ignimbrite and sandstone were non- developed Entisols. Illite was the dominant clay mineral found in ignimbrite and sandstone in both the A horizon and parent material. In loess derived soils however, smectite was dominant especially in the Bt horizon compared to its parent material indicating partly to its pedogenic formation. In limestone, illite and vermiculite were dominant both in the A and C horizons. Ti/Zr ratio proved that the studied soils were closely related to their underlying parent materials geochemically. Chemical index of alteration （CIA）, micromorphological index of soil development （MISECA）, smectite/illite＋chlorite ratio and magnetic susceptibility were applied to investigate the degree of soil development. Results showed that the most and the least developed soils were those formed on loess deposits and limestone,respectively. Application of the different geochemical and pedogenetic approaches was proved to be useful in identifying the relevance of soils to their underlying parent materials and also their degree of development.

Soil Organic Carbon Stock as Affected by Land Use/Cover Changes in the Humid Region of Northern Iran

【Title】【Author】This study was conducted to determine the changes in the soil carbon stocks as influenced by land use in a humid zone of Deylaman district （10,876 ha）, a mountainous region of northern Iran. For this, land use maps were produced from TM and ETM＋ images for 1985, 2000 and 2010 years; and this was supplemented by field measurement of soil carbon in 2010. The results showed that the mean soil organic carbon （SOC） density was 6.7±1.8 kg C m-2, 5.2±3.4 kg C m-2 and 3.2±1.8 kg C m-2 for 0-20 cm soil layer and 4.8±1.9 kg C m-2, 3.1±2 kg C m-2 and 2.7±1.8 kg C m-2 for 20-40 cm soil layer in forest, rangeland and cultivated land, respectively. During the past 25 years, 14.4% of the forest area had been converted to rangeland; and 28.4% of rangelands had been converted to cultivated land. According to the historical land use changes in the study area, the highest loss of SOC stocks resulted from the conversion of the forest to rangeland （0.45×104 Mg C in 0-40 cm depth layer）; and the conversion of rangeland to cultivated land （0.37×104 Mg C in 0-40 cm）, which typically led to the loss of soil carbon in the area studied. The knowledge on the historical land use changes and its influence on overall SOC stocks could be helpful for making management decision for farmers and policy managers in the future, for enhancing the potential of C sequestration in northern Iran.

Soil Organic Carbon Pools in Particle-Size Fractions as Affected by Slope Gradient and Land Use Change in Hilly Regions,Western Iran

This study was conducted to explore the effects of topography and land use changes on particulate organic carbon(POC),particulate total nitrogen(PTN),organic carbon(OC) and total nitrogen(TN) associated with different size primary particle fractions in hilly regions of western Iran.Three popular land uses in the selected site including natural forest(NF),disturbed forest(DF) and cultivated land(CL) and three slope gradients(0-10 %,S1,10-30 %,S2,and 30-50%,S3) were employed as the basis of soil sampling.A total of 99 soil samples were taken from the 0-10 cm surface layer in the whole studied hilly region studied.The results showed that the POC in the forest land use in all slope gradients was considerably more than the deforested and cultivated lands and the highest value was observed at NF-S1 treatment with 9.13%.The values of PTN were significantly higher in the forest land use and in the down slopes(0.5%) than in the deforested and cultivated counterparts and steep slopes(0.09%) except for the CL land use.The C:N ratios in POC fraction were around 17-18 in the forest land and around 23 in the cultivated land.In forest land,the silt-associated OC was highest among the primary particles.The enrichment factor of SOC,EC,was the highest for POC.For the primary particles,EC of both primary fractions of silt and clay showed following trend for selected land uses and slope gradients:CL> DF> NF and S3 > S2> S1.Slope gradient of landscape significantly affected the OC and TN contents associated with the silt and clay particles,whereas higher OC and TN contents were observed in lower positions and the lowest value was measured in the steep slopes.Overall,the results showed that native forest land improves soil organic carbon storage and can reduce the carbon emission and soil erosion especially in the mountainous regions with high rainfall in west of Iran.

Relationships between Soil Depth and Terrain Attributes in a Semi Arid Hilly Region in Western Iran

Soil depth generally varies in mountainous regions in rather complex ways.Conventional soil survey methods for evaluating the soil depth in mountainous and hilly regions require a lot of time,effort and consequently relatively large budget to perform.This study was conducted to explore the relationships between soil depth and topographic attributes in a hilly region in western Iran.For this,one hundred sampling points were selected using randomly stratified methodology,and considering all geomorphic surfaces including summit,shoulder,backslope,footslope and toeslope;and soil depth was actually measured.Eleven primary and secondary topographic attributes were derived from the digital elevation model(DEM) at the study area.The result of multiple linear regression indicated that slope,wetness index,catchment area and sediment transport index,which were included in the model,could explain about 76 % of total variability in soil depth at the selected site.This proposed approach may be applicable to other hilly regions in the semi-arid areas at a larger scale.

Paleopedology and magnetic properties of Sari loess-paleosol sequence in Caspian lowland, northern Iran

The objective of this study was to characterize the morphological and magnetic properties of Sari loess-paleosol section in northern Iran for paleopedologic and paleoenvironmental interpretation.The section consisted of a modern soil(MS)and three paleosols(PS1,PS2,PS3)separated by loess layers(LS1,LS2 and LS3).Based on particle size distribution,clay mineralogy,carbonates distribution and size of secondary carbonates,pedogenic development of the soils was in order of PS3>PS2>PS1=MS.Presence of redoximorphic features in PS3 was attributed to alternate stagnic saturation due to local water or high precipitation.Dominance of smectite and vermiculite as well as large carbonated dolls in PS3 indicated suitable environment and sufficient time for pedogenic development.Magnetic properties(χlf andχfd%)were distinctly higher in MS,PS1 and PS2 when compared to loess layers.The Lowest magnetic properties values were observed in PS3 which can be the result of ferrimagnetic minerals destruction under hydromorphic conditions.The highest Fed content occurred in PS3,however,lowχlf/Fed ratio indicated that majority of the iron minerals in PS3 are not magnetic.In conclusion,the particle size distribution,clay mineralogy and carbonates features were indicative of pedogenesis intensity,whereas,magnetic properties were useful to characterize the pedogenic environment.

Effects of environmental factors on classification of loessderived soils and clay minerals variations, northern Iran

Land-use type under different topographic conditions and human activities affects soil development. We investigated the effects of land-use,topography and human activity on soil classification changes in the Toshan watershed in northern Iran.Seven representative pedons derived from loess parent materials were studied on different land-uses and topographic positions. The studied pedons in forest(FO) on backslopes and footslope were classified as Calcic Haploxeralfs and Typic Haploxeralfs, respectively. The soils in abandoned lands(AB) and orchards(OR), where formerly under natural forests, located on the shoulder and backslopes positions were classified as Calcic Haploxeralfs and Vertic Haploxeralfs, respectively.Well-developed argillic horizons as indicators for higher degrees of soil evolution were observed in more-stable areas under the natural forest or less disturbed areas. Clay lessivage through these soil profiles have led to formation of Typic or Calcic Haploxeralfs, while under croplands(CP) were classified as Typic Calcixerepts. Conversion of sloping deforested areas to CP along with inappropriate management have accelerated soil erosion, resulting in unstable conditions in which decalcification and formation of developed soils cannot occur. Paddy cultivation in flat areas has caused to reduced conditions and formation of Typic Haplaquepts.Because of unfavorable conditions for chemical weathering(e.g. lower water retention compared to more-stable areas) no vermiculite was detected in the CP. The results showed that evolution and classification of the studied soils were strongly affected by land-use type, topography and management.

Soil Atterberg Limits and Consistency Indices as Influenced by Land Use and Slope Position in Western Iran

Atterberg limits and consistency indices are used for classifications of cohesive(fine-grained) soils in relation with compaction and tillage practices. They also provide information for interpreting several soil mechanical and physical properties such as shear strength, compressibility, shrinkage and swelling potentials. Although, several studies have been conducted regarding the land use effects on various soil mechanical properties, little is known about the effects of land use and slope positions on Atterberg limits and consistency indices. This study was conducted to investigate the effects of land use and slope position on selected soil physical and chemical properties, Atterberg limits and consistency indices in hilly region of western Iran. Three land uses including dryland farming, irrigated farming and pasture and four slope positions(i.e., shoulder, backslope, footslope, and toeslope) were used for soil samplings. One hundred eleven soil samples were collected from the surface soil(0-10 cm). Selected physical and chemical properties, liquid limit(LL), plastic limit(PL) and shrinkage limit(SL) were measured using the standard methods; and consistency indices including plastic index(PI), friability index(FI), shrinkage index(SI) and soil activity(A=PI/clay) were calculated. The results showed that irrigated farming significantly increased organic matter content(OM) and OM/clay ratio, and decreased bulk density(ρb) and relative bulk density(ρb-rel) as a result of higher biomass production and plant residues added to the soil compared to other land uses. Except for sand content, OM, ρb, cation exchange capacity(CEC) and calcium carbonate equivalent(CCE), slope position significantly affected soil physical and chemical properties. The highest values of silt, OM/clay and CEC/clay were found in the toeslope position, predominantly induced by soil redistribution within the landscape. The use of complexed(COC)- noncomplexed organic carbon(NCOC) concept indicated that majority of the studied soils were located below the saturation line and the OM in the soils was mainly in the COC form. The LL, PI, FI and A showed significant differences among the land uses; the highest values belonged to the irrigated farming due to high biomass production and plant residues returned to the soils. Furthermore, slope position significantly affected the Atterberg limits and consistency indices except for SL. The highest values of LL, PI, SI and A were observed in the toeslope position probably because of higher OM and CEC/clay due to greater amount of expandable phyllosilicate clays. Overall, soils on the toeslope under irrigated farming with high LL and SI and low values of FI need careful tillage management to avoid soil compaction.

Development and magnetic properties of loess-derived forest soils along a precipitation gradient in northern Iran

In order to investigate the development of forest soils formed on loess, six representative modern soil pedons were selected along a precipitation gradient extending from eastern Golestan(mean annual precipitation, MAP = 500 mm)to eastern Mazandaran Provinces(MAP = 800 mm).Physiochemical, micromorphological and magnetic properties, as well as clay mineralogy of soils were studied using standard methods. Soils are mainly classified as Alfisols and Mollisols. Downward decalcification and the subsequent clay illuviation were the main criteria of soil development in all study areas. Pedogenic magnetic susceptibility of pedons studied varied systematically across the precipitation gradient in Northern Iran, increasing from 14.66 ×10-8 m3 kg-1 at the eastern part to 83.75 × 10-8 m3 kg-1 at the western margin of this transect. The frequencydependent magnetic susceptibility showed an increasing trend with rainfall as well. The micromorphological study of soils indicated that there is a positive relationship between climate gradient (increasing rainfall) and the micromorphological index of soil development(MISECA). The area and thickness of clay coatings showed an increasing trend with rainfall. Grain size analysis indicates that pedogenic processes are responsible for changing original grain size distribution of loess in our soils.The correlation achieved among modern soil properties and precipitation could be applied to the buried paleosols in the whole study area to refer degree of paleosol development and to reconstruct the paleoclimate.

Digital mapping of soil physical and mechanical properties using machine learning at the watershed scale

Knowledge about the spatial distribution of the soil physical and mechanical properties is crucial for soil management,water yield,and sustainability at the watershed scale;however,the lack of soil data hinders the application of this tool,thus urging the need to estimate soil properties and consequently,to perform the spatial distribution.This research attempted to examine the proficiency of three machine learning methods(RF:Random Forest;Cubist:Regression Tree;and SVM:Support Vector Machine)to predict soil physical and mechanical properties,saturated hydraulic conductivity(Ks),Cohesion measured by fall-cone at the saturated(Psat)and dry(Pdry)states,hardness index(HI)and dry shear strength(SS)by integrating environmental variables and soil features in the Zayandeh-Rood dam watershed,central Iran.To determine the best combination of input variables,three scenarios were examined as follows:scenarioⅠ,terrain attributes derivative from a digital elevation model(DEM)+remotely sensed data;scenarioⅡ,covariates of scenarioⅠ+selected climatic data and some thematic maps;scenarioⅢ,covariates in scenarioⅡ+intrinsic soil properties(Clay,Silt,Sand,bulk density(BD),soil organic matter(SOM),calcium carbonate equivalent(CCE),mean weight diameter(MWD)and geometric weight diameter(GWD)).The results showed that for Ks,Psat Pdry and SS,the best performance was found by the RF model in the third scenario,with R2=0.53,0.32,0.31 and 0.41,respectively,while for soil hardness index(HI),Cubist model in the third scenario with R2=0.25 showed the highest performance.For predicting Ks and Psat,soil characteristics(i.e.clay and soil SOM and BD),and land use were the most important variables.For predicting Pdry,HI,and SS,some topographical characteristics(Valley depth,catchment area,mltiresolution of ridge top flatness index),and some soil characteristics(i.e.clay,SOM and MWD)were the most important input variables.The results of this research present moderate accuracy,however,the methodology employed provides quick and costeffective information serving as the scientific basis for decision-making goals.

Impacts of oak deforestation and rainfed cultivation on soil redistribution processes across hillslopes using ^(137)Cs techniques

Background:As one of the main components of land-use change,deforestation is considered the greatest threat to global environmental diversity with possible irreversible environmental consequences.Specifically,one example could be the impacts of land-use changes from oak forests into agricultural ecosystems,which may have detrimental impacts on soil mobilization across hillslopes.However,to date,scarce studies are assessing these impacts at different slope positions and soil depths,shedding light on key geomorphological processes.Methods:In this research,the Caesium-137(^(137)Cs)technique was applied to evaluate soil redistribution and soil erosion rates due to the effects of these above-mentioned land-use changes.To achieve this goal,we select a representative area in the Lordegan district,central Iran.^(137)Cs depth distribution profiles were established in four different hillslope positions after converting natural oak forests to rainfed farming.In each hillslope,soil samples from three depths(0–10,10–20,and 20–50 cm)and in four different slope positions(summit,shoulder,backslope,and footslope)were taken in three transects of about 20m away from each other.The activity of ^(137)Cs was determined in all the soil samples(72 soil samples)by a gamma spectrometer.In addition,some physicochemical properties and the magnetic susceptibility(MS)of soil samples were measured.Results:Erosion rates reached 51.1 t·ha^(−1)·yr^(−1) in rainfed farming,whereas in the natural forest,the erosion rate was 9.3 t·ha^(−1)·yr^(−1).Magnetic susceptibility was considerably lower in the cultivated land(χhf=43.5×10^(−8)m^(3)·kg^(−1))than in the natural forest(χhf=55.1×10^(−8)m^(3)·kg^(−1)).The lower soil erosion rate in the natural forest land indicated significantly higher MS in all landform positions except at the summit one,compared to that in the rainfed farming land.The shoulder and summit positions were the most erodible hillslope positions in the natural forest and rainfed farming,respectively.Conclusions:We concluded that land-use change and hillslope positions played a key role in eroding the surface soils in this area.Moreover,land management can influence soil erosion intensity and may both mitigate and amplify soil loss.

Carbonates and organic matter in soils characterized by reflected energy from 350-25000 nm wavelength

The soil carbon pool which is the sum of soil organic carbon(SOC)and soil inorganic carbon(SIC)is the second largest active store of carbon after the oceans and it is an important component of the global carbon cycle.Hence,accurate estimation of SOC and SIC as important carbon reservoirs in terrestrial ecosystems using fast,inexpensive and non-destructive methods is crucial for planning different climate change policies.The aim of the current research was to examine the effectiveness of Vis-NIR(visible and near-infrared spectroscopy:350-2500 nm)and MIR(mid-infrared spectroscopy:4000-400 cm-1)to characterize and estimate soil organic matter(SOM)and carbonates as main components of soil carbon stocks in Juneqan,Charmahal va Bakhtiari,Iran.To do so,a total of 548 soil samples from this area were collected(October 2015)and analyzed in laboratory(August 2017).In order to develop models capable of predicting SOM and carbonates content,seven spectral preprocessing methods comprising Absorbance(Abs),De-trending(Det),Continuum removal(CR),Savitzky-Golay derivatives(SGD),standard normal variate transformation(SNV),multiplicative scatter correction(MSC)and Normalization by range(NBR)were conducted along with five multivariate methods including Random Forest(RF),Partial Least-Squares Regression(PLSR),Artificial Neural Network(ANN),Support Vector Machine(SVM)and Gaussian Process Regression(GPR).The content of carbonates caused spectral reflectance intensity to augment on several ranges of spectrum and strong absorption feature at 2338 nm in the Vis-NIR and 714,850,870,1796,2150 and 2510 cm-1 in the MIR spectra range.SOM absorbed energy in several ranges,but also showed specific peaks in MIR.Both facts are associated with the structure of carbonates and SOM and its interaction with energy.The best combination of preprocessing and calibration models for carbonates quantification in Vis-NIR spectra was Det/PLSR(R2=0.74,RPD=2.19,RMSE=6.45).For SOM,it was Det/PLSR(R2=0.82,RPD=2.41,RMSE=0.75).The Det/RF(R2=0.87,RPD=2.44,RMSE=0.66)for the quantification of SOM and MSC/RF(R2=0.84,RPD=2.84,RMSE=5.50)for carbonates in MIR spectra range showed the greatest results.The stronger occurrence of spectral bands in MIR as well as the specificity of the absorption features indicated that this range produced better predictions.The obtained results highlighted the significant role of soil spectroscopy technique in predicting SOC and soil carbonates as key components of soil carbon stocks in the study area.Therefore,this technique can be used as a more cost-effective,time saving and nondestructive alternative to traditional methods of soil analysis.

Mass Balance of Major Elements in Relation to Weathering in Soils Developed on Igneous Rocks in a Semiarid Region,Northwestern Iran

This study was conducted to evaluate the weathering intensity of the major soils developed on igneous rocks in semiarid region of northwestern Iran.Eight parent materials were selected including monzodiorite,alkali granite,granodiorite,syenite,pyroxene diorite,hornblende andesite,pyroxene andesite,and dacite.Representative soil profiles were described and soil samples were collected and analyzed for selected chemical and physical properties and total concentrations of major elements and Zr,V,Ti and Y.Bulk densities as well as Ti,Zr and V concentrations were used to estimate the strain factors and mass balance equations were used to quantify the net result of pedogenic weathering,i.e.elemental loss and gain.The results of clay content and pedogenic iron variability as well as index of compositional variability(ICV),chemical index of alteration(CIA) and,A-CN-K and MFW ternary plots showed that the soils developed on volcanic rocks(hornblende andesite> pyroxene andesite> dacite) were more weathered than those on the plutonic parent rocks(alkali granite,granodiorite,monzodiorite,syenite,pyroxene diorite).The results of mass balance calculations based on the strain factors revealed that the Ca and Na depleted during weathering progress mostly from plagioclase grains.In the semiarid regions Ca is precipitated as pedogenic calcite in the soil horizons.K and Mg depletion is less than Ca and Na especially in the profiles on the hornblende andesite with the highest clay and LOI content.The results of this study clearly suggest that the behavior of K and Mg during the weathering cannot only be explained by the disintegration of the primary minerals,since they are fixed on the secondary clay minerals.Iron did not change in the soils compared to the parent material and was precipitated as the pedogenic iron and conserved in the soil horizons.Overall,the results on the weathering indicators and major elements mass balance enrichment/depletion in the study area confirmed that the soil profiles developed on volcanic rocks are more weathered than those on the plutonic igneous rocks.

Digital mapping of soil phosphorous sorption parameters (PSPs) using environmental variables and machine learning algorithms

In this study some soil phosphorous sorption parameters(PSPs)by using different machine learning models(Cubist(Cu),random forest(RF),support vector machines(SVM)and Gaussian process regression(GPR))were predicted.The results showed that using the topographic attributes as the sole auxiliary variables was not adequate for predicting the PSPs.However,remote sensing data and its combination with soil properties were reliably used to predict PSPs(R^(2)=0.41 for MBC by RF model,R^(2)=0.49 for PBC by Cu model,R^(2)=0.37 for SPR by Cu model,and R^(2)=0.38 for SBC by RF model).The lowest RMSE values were obtained for MBC by RF model,PBC by SVM model,SPR by Cubist model and SBC by RF model.The results also showed that remote sensing data as the easily available datasets could reliably predict PSPs in the given study area.The outcomes of variable importance analysis revealed that among the soil properties cation exchange capacity(CEC)and clay content,and among the remote sensing indices B5/B7,Midindex,Coloration index,Saturation index,and OSAVI were the most imperative factors for predicting PSPs.Further studies are recommended to use other proximally sensed data to improve PSPs prediction to precise decision-making throughout the landscape.