Microbiomes of Top and Sub-Layers of Semi-Arid Soils in North-Eastern Nigeria Are Rich in Firmicutes and Proteobacteria with Surprisingly High Diversity of Rare Species

Borno state is the second largest state in Nigeria with over 70,000 square kilometers of diverse ecosystems including parts of the fertile Lake Chad basin. However, more than 2/3 of this landmass is threatened with drought, advancing desertification and degraded soils. Most restoration efforts involve revegetation, which in the past has met with limited success. Microbial communities of soils play a pivotal role in soil fertility and plant cover. We conducted the first metagenomic amplicon sequencing study, comparing two soil depths to determine whether soil bacteria abundance and diversity in the harsh bare soils were sufficient to sustain greening efforts. The goal was to glean insights to guide microbial inoculant formulation needed in the region. Samples from top (0 - 15 cm) and sub (16 - 65 cm) soils were collected from five strategic locations in the state. Using next generation Illumina sequencing protocols, total DNA extracted directly from the soils was sequenced and analyzed by QIIME. Metadata collected from site showed scorching temperatures of over 46?C, near zero moisture level and a pH of about 6 for top soil. At 65 cm depth, the temperature averaged 32?C with a pH of 5 and significantly higher soil moisture of 0.1%. The bacterial community structure was unexpectedly very diverse at both soil depths samples, recording a ChaO1 index ranging from 909 to 4296 and a Shannon diversity range of 3.54 to 6.33. The most abundant phyla in both soil depths were the Firmicutes and Proteobacteria;however the relative abundance of composite lower taxa was strikingly different. Operational taxonomic units and diversity indices were highest for top soils and were dominated by members of resilient groups of Actinobacteria, Firmucutes, Acidobacteria and numerous other less well-known taxa whose individual relative abundance did not exceed 3% of total population. The high diversity and richness of Proteobacteria (at 65 cm depth), some of which are key to soil fertility, suggest that revegetation efforts could be improved by shifting the gradient of these microbiota upwards using shades and micro-irrigation. Soils in semi-arid regions in Nigeria contain numerous operational taxonomic bacterial groups with potential thermophilic and drought genetic resources to be mined. Microbial community structure beneath the top soil appears stable and should be the target sample for the assessments of climatic change impact on microbial community structure in environments like this.

Numerical Study of Impacts of Soil Moisture on the Diurnal and Seasonal Cycles of Sensible/Latent Heat Fluxes over Semi-arid Region

The semi-arid regions, as climatic and ecosystem transitional zones, are the most vulnerable to global environmental change. Earlier researches indicate that the semi-arid regions are characterized by strong landatmosphere coupling in which soil moisture is the crucial variable in land surface processes. In this paper, we investigate the sensitivity of the sensible/latent heat fluxes to soil moisture during the growing season based on the enhanced observations at Tongyu in the Jilin province of China, a reference site of international Coordinated Energy and Water Cycle Observations Project （CEOP） in the semi-arid regions, by using a sophisticated land surface model （NCAR_CLM3.0）. Comparisons between the observed and simulated sensible/latent heat fluxes indicate that the soil moisture has obvious effects on the sensible/latent heat fluxes in terms of diurnal cycle and seasonal evolution. Better representation of the soil moisture could improve the model performance to a large degree. Therefore, for the purpose of simulating the land-atmosphere interaction and predicting the climate and water resource changes in semi-arid regions, it is necessary to enhance the description of the soil moisture distribution both in the way of observation and its treatment in land surface models.

Small-Scale Spatial Variability of Soil Nutrients and Vegetation Properties in Semi-Arid Northern China

A field experiment was conducted at Kezuohouqi County, Inner Mongolia Autonomous Region of China, which was located on the southeastern edge of the Horqin Sandy Land, to study the spatial variability of soil nutrients for a smallscale, nutrient-poor, sandy site in a semi-arid region of northern China; to investigate whether or not there were 'islands of fertility' at the experimental site; and to determine the key nutrient elements that sustained ecosystem stability. Results obtained from geostatistical analysis indicated that the spatial distribution pattern of soil total nitrogen (STN) was far different from those of soil organic matter (SOM), total phosphorus (STP), and total potassium (STK). Compared to SOM, STP, and STK, STN had a lower structural heterogeneity ratio and a longer range, while other elements were all similar. In addition, STN had an isotropic spatial structure, whereas the others had an anisotropic spatial structure. The spatial structure patterns of herbage species, cover,and height also differed, indicating that spatial variability was subjected to different ecological factors. Differences in the spatial variability patterns among soil nutrients and vegetation properties showed that soil nutrients for a small-scale were not the primary limiting factors that influenced herbage spatial distribution patterns. Incorporating spatial distribution patterns of tree species, namely, Pinus sylvestris var. mongolica Litv. and shrub Lespedeza bicolor Turcz. in a research plot and using fractal dimension,SOM, STP, and STK were shown to contribute to the 'islands of fertility' phenomenon, however STN was not, possibly meaning that nitrogen was a key limiting element. Therefore, during restoration of similar ecosystems more attention should be given to soil nitrogen.

STUDY ON THE MODEL FOR PREDICTING SOIL EROSION AND ITS APPLICATION IN ARID AREA

On the basis of analyzing the soil erosion factors in typical arid area basin, this article tries to build a model by using USLE (Universal Soil Loss Equation). The first step is to digitize the topographic map (1∶100?000) and form the DEM (Digital Elevation Model), then use them to obtain necessary data of topographic factors. The second step is to get main elements causing soil erosion through using Main Element Analyzing Program. The third step is to systematically analyze all factors of soil erosion by applying Grey Dynamic Model and Fuzzy Mathematics, and then take GIS software to draw the colored map in the way that different colors present different intensities of soil erosion. At last the regional change of soil erosion amount on the basis of the color map is analyzed.

Study on Soil Salinization Information in Arid Region Using Remote Sensing Technique

Extracting information about saline soils from remote sensing data is useful, particularly given the environmental significance and changing nature of these areas in arid environments. One interesting case study to consider is the delta oasis of the Weigan and Kuqa rivers, China, which was studied using a Landsat Enhanced Thematic Mapper Plus （ETM＋） image collected in August 2001. In recent years, decision tree classifiers have been successfully used for land cover classification from remote sensing data. Principal component analysis （PCA） is a popular data reduction technique used to help build a decision tree; it reduces complexity and can help the classification precision of a decision tree to be improved. A decision tree approach was used to determine the key variables to be used for classification and ultimately extract salinized soil from other cover and soil types within the study area. According to the research, the third principal component （PC3） is an effective variable in the decision tree classification for salinized soil information extraction. The research demonstrated that the PC3 was the best band to identify areas of severely salinized soil; the blue spectral band from the ETM＋ sensor （TM1） was the best band to identify salinized soil with the salt-tolerant vegetation of tamarisk （Tamarix chinensis Lour）; and areas comprising mixed water bodies and vegetation can be identified using the spectral indices MNDWI （modified normalized difference water index） and NDVI （normalized difference vegetation index）. Based upon this analysis, a decision tree classifier was applied to classify landcover types with different levels of soil saline. The results were checked using a statistical accuracy assessment. The overall accuracy of the classification was 94.80%, which suggested that the decision tree model is a simple and effective method with relatively high precision.

Interaction between Cd and Pb in the soil-plant system: a case study of an arid oasis soil-cole system

The Hexi Corridor,our study area,is located in Northwest China and is also the most developed area of oasis farming in arid regions of Northwestern China.However,the rapid development of metallurgy and chemical industries in this region poses a great threat to the accumulation of heavy metals in crops.The objectives of this study are(1)to determine the influence of heavy metals on plant growth;(2)to assess the translocation capability of heavy metals in soil-plant system;and(3)to investigate the interaction between heavy metals.Pot experiments were conducted on cole(Brassica campestris L.)grown in the arid oasis soils singly and jointly treated with cadmium(Cd)and lead(Pb).Nine treatments were applied into the pots.Under the same planting conditions,three scenarios of Cd,Pb and Cd–Pb were designed to compare the interaction between Cd and Pb.The results showed that the response of cole weights to Cd,Pb and Cd–Pb treatments was slight,while Cd and Pb uptakes in cole were more sensitive to the single effects of Cd and Pb concentration in soils from the lower treatment levels.Under the influence of the single Cd,Pb and joint Cd–Pb treatments,Cd concentrations were lower in the cole roots than in the shoots,while for Pb,the results were opposite.Comparison studies revealed that the interaction of Cd and Pb could weaken the cole’s ability to uptake,concentrate and translocate heavy metals in arid oasis soils.

Toxic metal enrichment characteristics and sources of arid urban surface soil in Yinchuan City, China

To investigate the environmental quality of the urban surface soil in Yinchuan City, the capital of Ningxia Hui Autonomous Region （Ningxia）, China, we sampled surface soil and measured the concentrations of 8 toxic metals （Pb, Cr, Cu, Zn, Co, Bi, Ni and V） using X-ray fluorescence spectrometry. The enrichment characteristics and sources of these toxic metals in the soil were analyzed by the enrichment factor （EF） and multivariate statistical analysis. The results showed that the mean concentrations of these toxic metals in the soil samples were 25.0, 109.1, 16.8, 26.0, 37.2, 2.7, 25.3 and 59.9 mg/kg for Pb, Cr, Cu, Zn, Co, Bi, Ni and V, respectively, which were 1.2, 1.8, 0.8, 0.4, 3.2, 8.7, 0.7 and 0.8 times of the corresponding background values of Ningxia soil, respectively. The variations of Pb, Zn, Co, Bi and Ni concentrations in the surface soil of Yinchuan were larger than those of the other metals. Our results also showed that the toxic metals investigated in the soil had different enrichment levels. Both Co and Bi were significantly enriched, whereas Cr was only moderately enriched in the soil. There was a deficiency or minimal enrichment of the other toxic metals in the soil. Source analysis results based on the concentration, enrichment characteristics and multivariate statistical analysis indicated that Cr, V and Ni originated from a combination of fossil fuel combustion, traffic pollution and natural occurrence. Pb, Cu and Zn were predominantly derived from natural and traffic sources, while Co and Bi primarily originated from construction sources.

IRRIGATING WARPED SOILS——ANTHROPOGENIC SOIL IN ARID AND SEMI-ARID REGIONS OF CHINA

The irrigating warped soils occur in the old irrigation areas of arid and semi-arid re-gions of China, and distributed from Zhangjiakou of Hebei province, through InnerMongolia Autonomous Region, Ningxia Hui Autonomous Region, Gansu province,Qinhai Province, down to Xinjiang Autonomous Region, including the arid subalpine rivervalleys in the western part of Tibet.

SOIL SALINIZATION AND ITS COUNTERMEASURE IN ARID DISTRICT

1. Present Situation All the Hetao irrigation district covers an area of 24.8 thousand sq.km, including thecultivited area of 345.4 thousand ha. It is the greatest gravity irrigation district drawing theYellow Rive’s water in North China.

Application of Bio-Solids as Soil Amendment in Arid Rangeland of Jordan

Due to long drought periods and over utilizing of range lands in the arid lands of Jordan, the land is degraded and lost most of its natural vegetation. To rehabilitate the natural vegetation cover, there is a need to enhance the fertility of soil to be able to support vegetation under limited amounts of rainfall. One of the available and viable options that might be able to provide a solution for the soil poverty is applying materials with high organic contents such as biosolid. Bio-solids are nutrient-rich organic materials from the treatment of domestic sewage in a wastewater treatment facility. Bio-solids are a beneficial resource, containing essential plant nutrients and organic matter and are recycled as a fertilizer and soil amendment. A pilot study is designed based on randomized block design in which five treatments are used to represent the loading rates of bio-solids application. These loads were 10, 20, 30, 40 and 50 tons/ha with four replicates for the control and each application load. Samples from Bio-solid, soil and plants are tested for chemicals and microbes. Chemical tests include: As, Cd, Cr, Co, Cu, Hg, Mo, Ni, Pb, Se, and Zn, while microbial tests include: total fecal Coliform, Salmonella, and Helminthes eggs. Results of total microbial count in bio-solids, soil and plant samples indicated that there were no detectable counts found in all of the experimental plots. Results showed increase in most of the heavy metals concentration in soil treated with bio-solids from that of soil in control plots;some of these elements doubled after applying the bio-solid. For the dry plant matter, analysis for heavy metals showed that most of the heavy metals studied were below the detection limit. Only the Cr, Cu and Zn are changed but not significantly compared with the control plot. Results obtained were showed that the highest dry biomass value was obtained with bio-solids loading rate 40 tons/ha and more. Increasing rate of application after 40 tons/ha did not show significant differences in the biomass yield. Also, the total nitrogen in the plants increased by 40% for all bio-solid application loads compared with the control lot.

Crop yields and soil organic carbon dynamics in a long-term fertilization experiment in an extremely arid region of northern Xinjiang, China

A long-term fertilization experiment was set up in northern Xinjiang, China to evaluate the dynamics of crop production and soil organic carbon （SOC） from 1990 to 2012 with seven fertilization treatments. The seven treatments included an unfertilized control （CK） and six different combinations of phosphorus （P）, potassium （K）, nitrogen （N）, straw （S） and animal manure （M）. The balanced fertilization treatments had significantly （P〈0.05） higher average yields than the unbalanced ones. The treatment with 2/3 N from potassium sulfate （NPK） and 1/3 N from farmyard manure （NPKM） had a higher average yield than the other treatments. The average yields （over the 23 years） in the treatments of NPK, and urea, calcium superphosphate （NP） did not differ significantly （P〉0.05） but were higher than that in the treatment with urea and potassium sulfate （NK; P〈0.05）. The results also show that the highest increases in SOC （P〈0.05） occurred in NPKM with a potential increase of 1.2 t C/（hm2.a）. The increase in SOC was only 0.31, 0.30 and 0.12 t C/（hm2.a） for NPKS （9/10 N from NPK and 1/10 N from straw）, NPK and NP, respectively; and the SOC in the NP, NK and CK treatments were approaching equilibrium and so did not rise or fall significantly over the 23-year experiment. A complete NPK plus manure fertilization program is recommended for this extremely arid region to maximize both yields and carbon sequestration.

Effects of cotton field management practices on soil CO2 emission and C balance in an arid region of Northwest China

Changes in both soil organic C storage and soil respiration in farmland ecosystems may affect atmospheric CO2 concentration and global C cycle. The objective of this field experiment was to study the effects of three crop field management practices on soil CO2 emission and C balance in a cotton field in an arid region of Northwest China. The three management practices were irrigation methods（drip and flood）, stubble managements（stubble-incorporated and stubble-removed） and fertilizer amendments（no fertilizer（CK）, chicken manure（OM）, inorganic N, P and K fertilizer（NPK）, and inorganic fertilizer plus chicken manure（NPK＋OM））. The results showed that within the C pool range, soil CO2 emission during the whole growing season was higher in the drip irrigation treatment than in the corresponding flood irrigation treatment, while soil organic C concentration was larger in the flood irrigation treatment than in the corresponding drip irrigation treatment. Furthermore, soil CO2 emission and organic C concentration were all higher in the stubble-incorporated treatment than in the corresponding stubble-removed treatment, and larger in the NPK＋OM treatment than in the other three fertilizer amendments within the C pool range. The combination of flood irrigation, stubble incorporation and application of either NPK＋OM or OM increased soil organic C concentration in the 0-60 cm soil depth. Calculation of net ecosystem productivity（NEP） under different management practices indicated that the combination of drip irrigation, stubble incorporation and NPK＋OM increased the size of the C pool most, followed by the combination of drip irrigation, stubble incorporation and NPK. In conclusion, management practices have significant impacts on soil CO2 emission, organic C concentration and C balance in cotton fields. Consequently, appropriate management practices, such as the combination of drip irrigation, stubble incorporation, and either NPK＋OM or NPK could increase soil C storage in cotton fields of Northwest China.

Spatial Variations of Soil Respiration in Arid Ecosystems

Soil respiration releases a major carbon flux back to atmosphere and thus plays an important role in global carbon cycling. Soil respiration is well known for its significant spatial variation in terrestrial ecosystems, especially in fragile ecosystems of arid land, where vegetation is distributed sparsely and the climate changes dramatically. In this study, soil respiration in three typical arid ecosystems: desert ecosystem (DE), desert-farmland transition ecosystem (TE) and farmland ecosystem (FE) in an arid area of northwestern China were studied for their spatial variations in 2012 and 2013. Along with soil respiration (SR), soil surface temperature (ST), soil moisture (SM) and soil electrical conductivity (ECb) were also recorded to investigate the spatial variations and the correlations among them. The results revealed that averaged soil respiration rate was much lower in DE than those in TE and FE. No single factor could adequately explain the variation of soil respiration, except a negative relationship between soil temperature and soil respiration in FE (P < 0.05). Geostatistical analysis showed that the spatial heterogeneity of soil respiration in DE was insignificant but notably in both TE and FE, especially in FE, which was mainly attributed to the different vegetation or soil moisture characteristics in the three ecosystems. The results obtained in this study will help to provide a better understanding on spatial variations of soil respiration and soil properties in arid ecosystems and also on macroscale carbon cycling evaluations.

Impact of aridization on soil cover transformation of the Aral Sea and the modern Syr-Darya Delta

The effects of human activities on the soil cover transformation in the eastern part of Kazakhstan were investigated during the period of 1956-2008.The results of the research for different soil types in Priaralye indicated that there was 643.3×103 hm2 solonchaks,accounting for 38.5 % of the total area（1670.5×10^3 hm^2） in 2008.Vast areas are occupied with dried lakeshore soil（311.1× 10^3 hm^2）,sandy soils（147.6×10^3 hm^2） and grey-brown desert soils and solonetzes（146.7×10^3 hm^2）.In 2001 the area of solonchak was 755×103 hm2 and decreased to 643.3×10^3 hm^2 in 2008,which due to the shrinkage of the Aral Sea,the areas of marsh and lakeshore solonchaks decreased with the increase of dried bottom of the Aral Sea.The level of soil cover transformation in the modern delta of the Syr-Darya River can be seen from the comparison of the results obtained from the different years in the study area.The area of solonchaks increased by 10×10^3 hm^2 and the area of alluvial-meadow salinizied soils increased by 17.9×10^3 hm^2 during the period of 1956-1969.It means that many non-salinizied soils were transformed into salinizied ones.Striking changes occurred in the structure of soil cover as a result of aridization.So,the researches in1969 significantly determined the areas of hydromorphic soils subjected to desertification（it was not fixed on the map before 1956）.Later,these soils were transformed into takyr-like soils.The area of takyr-like soils increased almost by 3 times for 34 years（from 1956 to 1990）.The long-term soil researches on soil cover transformation in Priaralye have shown that the tendencies of negative processes（salinization and deflation） are being kept and lead to further soil and eco-environment degradation in the region.

Soil water response to precipitation in different microtopographies on the semi-arid Loess Plateau,China

Soil water is an important factor restricting afforestation on the semi-arid Loess Plateau.The microtopography of the loess slope has changed the distribution pattern of soil water on the slope.To improve water utilization efficiency and optimize afforestation configuration patterns,the relationship between soil water and precipitation at micro-topographic scale must be studied.We used time series analysis to study the temporal variation of soil water and its response to precipitation in four kinds of micro-topographies and undisturbed slope on loess slopes.Micro-topographies significantly influenced soil water distribution and dynamics on the slopes.Soil water stored in the platform,sinkhole,and ephemeral gully influenced subsequent soil water for 4 weeks,whereas soil water stored in the scarp and undisturbed slope could influence soil water for 2 weeks.It took 12 weeks,10 weeks,18 weeks,6 weeks,and 12 weeks for precipitation to reach the deeper soil layer in the platform,sinkhole,scarp,ephemeral gully,and undisturbed slope,respectively.These soil water characteristics in different micro-topographies are vital factors that should be taken into consideration when undertaking afforestation on the Loess Plateau.

Spatial Distribution of Soil Organic Matter and Soil Organic Carbon Stocks in Semi-Arid Area of Northeastern Syria

Although soil organic matter (SOM) forms a small portion of the soil body. Nevertheless, it is the most important component of the soil ecosystem, as well as of the carbon global cycle. In the semi-arid environment, there has been little research on the spatial distribution of SOM and soil organic carbon (SOC) stock. In this study, stratified random samples of total 30 soils were collected from two different soil depth (topsoil, subsoil) of Al Balikh plain and used for mapping the spatial variability of SOC and to estimating the SOC stock. The result showed that the values were relatively homogenate, with the normal decreasing trend with increasing the depth. The standard deviation (Std. D) for both SOC and SOC stock indicates homogeneous and absence of outliers values, whereas the coefficient of variation (C.V) indicates non-dispersion and clustering of values around the average. SOC was 0.38%, 0.17% in topsoil and subsoil respectively;the corresponding averages of SOC stock were 1.23 kg·m-2? and 1.14 kg·m-2 respectively, these values reflecting typical characteristics of poor SOC semi-arid soil. The correlation between SOC and SOC stock was (R2 = 0.996, p 2 = 0.941, p < 0.001) for subsoil. The semivariograms were indicated that both SOC and SOC stock were best fitted to the exponential model. Nugget, range, and sill were equal to 0.002, 0.036, and 0.044, respectively for SOC in topsoil, and 0.014, 0.071, and 0.081, for SOC in the subsoil. For SOC stock, it was 0.0, 0.036, and 0.0508, respectively in topsoil. In the subsoil, the values were 0.1899, 0.086, and 4.159, respectively. SOC and SCO stock in both two layers are shown a strong spatial dependence, for which were 4.3, 17.2 for SOC in topsoil and subsoil respectively, and 0.0, 4.5 for SOC stock in topsoil and subsoil respectively, thus, which can be attributed to intrinsic factors.

Satellite-Based Monitoring of Decadal Soil Salinization and Climate Effects in a Semi-arid Region of China

Soil salinization is a common phenomenon that affects both the environment and the socio-economy in arid and semi-arid regions; it is also an important aspect of land cover change. In this study, we integrated multi-sensor remote sensing data with a field survey to analyze processes of soil salinization in a semi-arid area in China from 1979 to 2009. Generally, the area of salt-affected soils increased by 0.28% per year with remarkable acceleration from 1999 to 2009 （0.42% increase per year）. In contrast, the area of surface water bodies showed a decreasing trend （-0.08% per year） in the same period. Decreases in precipitation and increases in aridity due to annual （especially summer） warming provided a favorable condition for soil salinization. The relatively flat terrain favored waterlogging at the surface, and continuous drought facilitated upward movement of soil water and accumulation of surface saline and calcium. Meanwhile, land-use practices also played a crucial role in accelerating soil salinization. The conversion to cropland from natural vegetation greatly increased the demand for groundwater irrigation and aggravated the process of soil salinization. Furthermore, there are potential feedbacks of soil salinization to regional climate. The salinization of soils can limit the efficiency of plant water use as well as photosynthesis; therefore, it reduces the amount of carbon sequestrated by terrestrial ecosystem. Soil salinization also reduces the absorbed solar radiation by increasing land surface albedo. Such conversions of land cover significantly change the energy and water balance between land and atmosphere.

Comparative Study among Different Semi-Empirical Models for Soil Salinity Prediction in an Arid Environment Using OLI Landsat-8 Data

Salt-affected soils, caused by natural or human activities, are a common environmental hazard in semi-arid and arid landscapes. Excess salts in soils affect plant growth and production, soil and water quality and, therefore, increase soil erosion and land degradation. This research investigates the performance of five different semi-empirical predictive models for soil salinity spatial distribution mapping in arid environment using OLI sensor image data. This is the first attempt to test remote sensing based semi-empirical salinity predictive models in this area: the Kingdom of Bahrain. To achieve our objectives, OLI data were standardized from the atmosphere interferences, the sensor radiometric drift, and the topographic and geometric distortions. Then, the five semi-empirical predictive models based on the Normalized Difference Salinity Index (NDSI), the Salinity Index-ASTER (SI-ASTER), the Salinity Index-1 (SI-1), the Soil Salinity and Sodicity Index-1 and Index-2 (SSSI-1 and SSSI-2), developed for slight and moderate salinity in agricultural land, were implemented and applied to OLI image data. For validation purposes, a fieldwork was organized and different important spots-locations representing different salinity levels were visited, photographed, and localized using an accurate GPS (σ ≤ ±30 cm). Based on this a priori knowledge of the soil salinity, six validation sites were selected to reflect non-saline, low, moderate, high and extreme salinity classes, descriptive statistics extracted from polygons and/or transects over these sites were used. The obtained results showed that the models based on NDSI, SI-1 and SI-ASTER all failed to detect salinity bounds for both extreme salinity (Sabkhah) and non-saline conditions. In Fact, NDSI and SI-ASTER gave respectively only 35% dS/m and 25% dS/m in extreme salinity validation site, while SI-1 and SI-ASTER indicated 38% dS/m and 39% dS/m in non-saline validation site. Therefore, these three models were deemed inadequate for the study site. However, both SSSI-1 and SSSI-2 allowed a detection of the previous salinity bounds and furthermore described similarly and correctly the urban-vegetation areas and the open-land areas. Their predicted EC is around 10% dS/m for non-saline urban soil, about 25% dS/m for low salinity urban-vegetation soil, approximately 30% to 75% dS/m, respectively, for moderate to high salinity soils. SSSI-2 based semi-empirical salinity models was able to differentiate the high salinity versus extreme salinity in areas where both exist and was very accurate to highlight the pure salt where SSSI-1 has reach saturation for both salinity classes. In conclusion, reliable salinity map was produced using the model based on SSSI-2 and OLI sensor data that allows a better characterization of the soil salinity problem in an Arid Environment.

The Estimation of Soil Organic Matter Variation in Arid and Semi-Arid Lands Using Remote Sensing Data

Soil organic matter (SOM) is an important term to realize soil productivity and quality that is extremely influential on soil physical, chemical and biological processes;SOM is one of the key soil properties controlling nutrient budgets in agricultural production systems and is an important index of soil productivity. Remote sensing (RS) and Geographic Information System (GIS) techniques were used to assess organic matter in soil and determine the relationship between measures SOM in field and digital data to calculate or obtain the correlation coefficients applied to evaluate the strength and direction of the linear relationships. In this study Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Bare Soil Index (BSI) were used. The results show that the relationship between vegetation indices (NDVI, SAVI) and SOM in whole study area was (R2 = 0.19, p 2 = 0.01, p 2 = 0.13, p 2 = 0.11, p < 0.05), soil organic carbon increases with increasing NDVI and decreasing BSI. NDVI, SAVI and BSI were considered a useful index to detect the spatial distribution of SOM concentrations and mapping using remote sensing data.