Novel Hybrid X GBoost Model to Forecast Soil Shear Strength Based on Some Soil Index Tests

When building geotechnical constructions like retaining walls and dams is of interest,one of the most important factors to consider is the soil’s shear strength parameters.This study makes an effort to propose a novel predictive model of shear strength.The study implements an extreme gradient boosting(XGBoost)technique coupled with a powerful optimization algorithm,the salp swarm algorithm(SSA),to predict the shear strength of various soils.To do this,a database consisting of 152 sets of data is prepared where the shear strength(τ)of the soil is considered as the model output and some soil index tests(e.g.,dry unit weight,water content,and plasticity index)are set as model inputs.Themodel is designed and tuned using both effective parameters of XGBoost and SSA,and themost accuratemodel is introduced in this study.Thepredictionperformanceof theSSA-XGBoostmodel is assessedbased on the coefficient of determination(R2)and variance account for(VAF).Overall,the obtained values of R^(2) and VAF(0.977 and 0.849)and(97.714%and 84.936%)for training and testing sets,respectively,confirm the workability of the developed model in forecasting the soil shear strength.To investigate the model generalization,the prediction performance of the model is tested for another 30 sets of data(validation data).The validation results(e.g.,R^(2) of 0.805)suggest the workability of the proposed model.Overall,findings suggest that when the shear strength of the soil cannot be determined directly,the proposed hybrid XGBoost-SSA model can be utilized to assess this parameter.

Drivers of the Chemical Quality of Market Gardening Soils in the Urban and Peri-Urban Environment of Bobo-Dioulasso (Burkina Faso): Impact of Fertilizers Sources and Sites Location

Urban and peri-urban agriculture plays a key role by providing many goods and services. In particular, it provides diversified food and employment for vulnerable groups (youth and women). However, it often involves negative externalities due to non-conventional soils fertility management practices. This study aimed to investigate the chemical quality of soils over six (06) sites of the market gardening area of Bobo-Dioulasso (Burkina Faso) as affected by fertilizers uses and sites location. Thirty (30) representative market gardening farms, located in urban, semi-urban and rural areas, were randomly selected from a baseline survey database. Within each farm, composite soil samples made up of 3 individual cores were taken over the 0 - 15 cm soil depth for determining soils carbon, total nitrogen, available phosphorus contents and pH-water. These data were normalized and summarized to compute a synthetic Soil Fertility Index (SFI). The data processing was focused on a Principal Component Analysis and an Ascendant Hierarchical Classification in order to make a typology of the vegetable farms. Fertilizers management effects on soils quality were compared through Variance Analysis (ANOVA) following a GLM procedure in Rstudio software. As main results, soils chemical parameters, except for available K, were affected by the location of the sites. Soils in urban farms are less acidic (on average pH = 6.9), while semi-urban and rural sites (Samadeni, Nakaguana) have more acidic soils. However, the latter site had the highest values of C and N. Moreover, the long-term application of organic matter sources results in improving of the chemical quality of the market garden soil. The SFI is positively correlated with the rate of applied organic fertilizers, and the cultivation duration. On the other hand, soil quality tends to decrease with the expansion of the area, due to a dilution effect of the organic fertilizer doses. All these results suggest that there is a real scope to reinforce the position of the market garden as an opportunity for recycling organic wastes and sequestration of carbon by promoting relevant fertilization packages that strongly rely on organic matters sources (Compost, Biochar, etc.).

Soil Quality Assessment of Acid Sulfate Paddy Soils with Different Productivities in Guangdong Province,China

Land conversion is considered an effective measure to ensure national food security in China, but little information is available on the quality of low productivity soils, in particular those in acid sulfate soil regions. In our study, acid sulfate paddy soils were divided into soils with high, medium and low levels based on local rice productivity, and 60 soil samples were collected for analysis. Twenty soil variables including physical, chemical and biochemical properties were determined. Those variables that were significantly different between the high, medium and low productivity soils were selected for principal component analysis, and microbial biomass carbon （MBC）, total nitrogen （TN）, available silicon （ASi）, pH and available zinc （AZn） were retained in the minimum data set （MDS）. After scoring the MDS variables, they were integrated to calculate a soil quality index （SQI）, and the high, medium and low productivity paddy soils received mean SQI scores of 0.95, 0.83 and 0.60, respectively. Low productivity paddy soils showed worse soil quality, and a large discrepancy was observed between the low and high productivity paddy soils. Lower MBC, TN, ASi, pH and available K （AK） were considered as the primary limiting factors. Additionally, all the soil samples collected were rich in available P and AZn, but deficient in AK and ASi. The results suggest that soil AK and ASi deficiencies were the main limiting factors for all the studied acid sulfate paddy soil regions. The application of K and Si on a national basis and other sustainable management approaches are suggested to improve rice productivity, especially for low productivity paddy soils. Our results indicated that there is a large potential for increasing productivity and producing more cereals in acid sulfate paddy soil regions.

Soil Moisture Retrieval from Satellite Images and Its Application to Heavy Rainfall Simulation in Eastern China

The soil water index （SWI） from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient （CORR）, root-mean-square-error （RMSE） and bias （BIAS） shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture （NCEP） in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model＇s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy ralnfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.

Changes in Organic Carbon Index of Grey Desert Soil in Northwest China After Long-Term Fertilization

Soil organic carbon （SOC）, soil microbial biomass carbon （SMBC） and SMBC quotient （SMBC/SOC, qSMBC） are key indexes of soil biological fertility because of the relationship to soil nutrition supply capacity. Yet it remains unknown how these three indexes change, which limits our understanding about how soil respond to different fertilization practices. Based on a 22-yr （1990-2011） long-term fertilization experiment in northwest China, we investigated the dynamics of SMBC and qSMBC during the growing period of winter wheat, the relationships between the SMBC, qSMBC, soil organic carbon （SOC） concentrations, the carbon input and grain yield of wheat as well. Fertilization treatments were 1） nonfertilization （control）; 2） chemical nitrogen plus phosphate plus potassium （NPK）; 3） NPK plus animal manure （NPKM）; 4） double NPKM （hNPKM） and 5） NPK plus straw （NPKS）. Results showed that the SMBC and qSMBC were significantly different among returning, jointing, flowering and harvest stages of wheat under long-term fertilization. And the largest values were observed in the flowering stage. Values for SMBC and qSMBC ranged from 37.5 to 106.0 mg kg1 and 0.41 to 0.61%, respectively. The mean value rank of SMBC during the whole growing period of wheat was hNPKM〉NPK_M〉NPKS〉CK〉NPK. But there were no statistically significant differences between hNPKM and NPKM, or between CK and NPK. The order for qSMBC was NPKS〉NPKM〉CK〉hNPKM〉NPK. These results indicated that NPKS significantly increased the ratio of SMBC to SOC, i.e., qSMBC, compared with NPK fertilizer or other two NPKM fertilizations. Significant linear relationships were observed between the annual carbon input and SOC （P〈0.01） or SMBC （P〈0.05）, and between the relative grain yield of wheat and the SOC content as well （P〈0.05）. But the qSMBC was not correlated with the annual carbon input. It is thus obvious that the combination of manure, straw with mineral fertilizer may be benefit to increase SOC and improve soil quality than using only mineral fertilizer.

Soil Fertility Comparison between Rotations of Tobacco-Rice (TR) and Rape-Rice (RR)

Tobacco-planting plays an important role in ensuring the high-quality tobacco raw materials supply and the local social and economic development in Chenzhou City. In recent years whether tobacco-planting is better for the maintenance and improvement of soil fertility than other crop-planting has been highly concerned. In this study, 16 soil fertility indicators and soil integrated index (IFI) were compared by 21 pairs of fields in Chenzhou city under the rotations of tobacco-rice (TF) and rice-rice (RR), and results showed that, comparing the mean values of soil fertility indicators, the contents of OM, TN, AN, AK, S and IFI were extremely significantly higher in TR than those in RR (p < 0.01), the contents of Cu, Ca, Mg and Fe were significantly higher in TR than those in RR (p < 0.05), but Mn content was significantly lower in TR than those in RR (p < 0.05). Meanwhile the contents of TP, TK and AP were insignificantly higher in TR than those in RR, and the contents of B, Mo and Zn were insignificantly lower in TR than those in RR. The above significant differences in soil fertility indicators were mainly due to relatively higher fertilizer inputs and less nutrient removal during tobacco-growing season than during rape-growing season, the net increase of N, P2O5 and K2O are 8.61, 5.25 and 24.89 kg per 667 m2 respectively in tobacco-growing season, while the net decrease of N, P2O5 and K2O are 8.88, 4.70 and 4.62 kg per 667 m2 respectively in rape-growing season. C.V. of soil fertility indicators and IFI were meanly lower in TR (52.25% and 15.95%, respectively) than those in RR (63.07% and 22.12%, respectively). Comparatively, tobacco-planting can improve soil fertility better than rape-planting when rotated with late rice in Chenzhou city. For tobacco-planting, Mg fertilizer should be applied for 23.8% TR fields, while more N, K, Ca, Mg, S and B fertilizers should be applied for 42.86%, 23.81%, 14.29%, 47.62%, 80.95% and 47.62% RR fields, respectively.

Soil quality index as a tool for Scots pine(Pinus sylvestris) monoculture conversion planning on afforested,reclaimed mine land

In Central Europe, a large portion of post-mining sites were afforested with Scots pine, which is characterized by good adaptability and a tolerance for poor habitat at the beginning of forest ecosystem development. Conversion of monoculture on mine sites into more biodi- verse mixed hardwood forests, especially on more fertile deposits, can be an emerging need in this part of Europe in next decades. The ability to classify the forests at these post-mining sites will facilitate proper species selection as well as the management and formation of the developed ecosystem＇s stability. This work describes the guidelines that can be followed to assess reclaimed mine soil （RMS） quality, using the mine soil quality index （MSQI） and a classification of developed forest sites as a basis of tree-stand species selection and conversion of pine monocul- tures. The research was conducted on four post-mining facilities （lignite, hard coal, sulphur, and sand pit mining areas） on different RMS sub- strates dominant in Central Europe. Soil quality assessment takes into account the following features of the soil： texture soil nutrients （Ca, Mg, K, Na, P）; acidity （pH KC1）; and Corg-to-Nt ratio in the initial organic horizon. An analysis was conducted of classification systems using the MSQI validation correlation （at p =0.05） with vegetation features af- fected by succession： aboveground biomass of forest floor and ecological indicators of vascular plants （calculated on the basis of EUenberg＇s （2009） system）. Eventually, in the analysed data set, the MSQI ranged from 0.270 for soils on quaternary sands to 0.720 for a mix of quaternary loamy sands with neogene clays. Potential forest habitat types and the role of the pine in the next generation of tree stands on different RMS parent rock substrate were proposed.

Estimation of the Biological Methods of Assessing Soil N-Supplying Capacity in Calcareous Soil

Although many biological methods are used to determine soil nitrogen supplying capacity, there are certain differences in the results for different types of soils and various ways of measurement due to the complexity of soil N conformation, the high variance of soil and microorganism, and the difference of environment. Therefore, it is not clear about which biologic incubation method is better for calcareous soil. In this study, pot experiments were performed by using 25 different calcareous surface soil samples on the Loess Plateau and taking the N uptake of wheat and corn with leaching soil initial nitrate and without leaching in pot experiments as the control to investigate the difference of eight biological incubation methods for reflecting soil nitrogen supply capacity. The eight biological methods are waterlogged incubation, aerobic incubation for 2 weeks and for 4 weeks, dry-wet alternation aerobic incubation for 2 weeks, long-term alternate leaching aerobic incubation （and N mineralization potential, No）, short-term leaching aerobic incubation, microbial biomass carbon （Bc）, and microbial biomass nitrogen （BN） method, respectively. Among these methods, the dry-wet alternation aerobic incubation and aerobic incubation for 4 weeks were the modification of the method of aerobic incubation for 2 weeks according to the actual farmland moisture. The results showed that the correlation coefficients between these methods and crop uptake N with leaching soil initial nitrate were 0.530, 0.700, 0.777, 0.768, 0.764 （and 0.790, No）, 0.650, 0.555, and 0.465, respectively （r0.05 = 0.369, r0.0l = 0.505）. While without leaching soil initial nitrate, their coefficients were 0.351, 0.963, 0.962, 0.959, 0.825 （and0.812, No）, 0.963, 0.289, and 0.095, respectively （r0.05 = 0.369, r0.01 = 0.505）. In conclusion, excluding the soil initial nitrate, the correlation coefficients between the eight methods and crop uptake N were, from high to low, N0, aerobic incubation for 4 weeks, dry-wet alternation aerobic incubation for 2 weeks, and long-term alternate leaching aerobic incubation, while including the soil initial nitrate the correlation coefficients between them increased significantly and the values were all beyond 0.950 for these four methods, including aerobic incubation for 2 weeks and for 4 weeks, dry-wet alternation aerobic incubation for 2 weeks and short-term leaching aerobic incubation. The waterlogged incubation method, Bc and BN in the calcareous soil, had lower correlation coefficient with crop uptake nitrogen compared with other methods. Thus, dry-wet alternation aerobic incubation for 2 weeks was a better index for evaluating calcareous soil N supply capacity due to some other methods having disadvantages and not suitable for the actual farmland characteristics.

Characterization of Orchard Fields Based on Soil Fertility Index (SOFIX)

Soil samples from 139 agricultural orchard fields (apple, grape, tea, and others) were analyzed using the soil fertility index. From these samples, an orchard field database was constructed and the soil properties between orchard, upland, and paddy fields were compared. The average value of bacterial biomass in the orchard fields was 7.4 × 108 cells/g-soil, ranging from not detected (lower than 6.6 × 106 cells/g-soil) to 7.7 × 109 cells/g-soil. The average values of total carbon (TC), total nitrogen (TN), total phosphorus (TP), and total potassium (TK), were 24,000 mg/kg (2670 to 128,100 mg/kg), 1460 mg/kg (133 to 6400 mg/kg), 1030 mg/kg (142 to 5362 mg/kg), and 5370 mg/kg (1214 to 18,155 mg/kg), respectively. The C/N and C/P ratios were 19 (3 to 85) and 27 (2 to 101), respectively. Soil properties of the orchard fields were compared with those of the upland and the paddy fields. The average value of bacterial biomass in the orchard fields was almost the same as that in the upland fields (8.0 × 108 cells/g-soil), but the number was lower than that in the paddy fields (12.9 × 108 cells/g-soil). The average values of TC and TN in the orchard fields fell between those in the upland fields (TC: 33,120 mg/kg, TN: 2010 mg/kg) and the paddy fields (TC: 15,420 mg/kg, TN: 1080 mg/kg). The relationship between the bacterial biomass and TC in the orchard fields resembled that in the upland fields. A suitable soil condition for the orchard fields was determined as TC: ≥25,000 mg/kg, TN: ≥1500 mg/kg, TP: ≥900 mg/kg and TK: 2500 - 10,000 mg/kg. These recommended values will be effective for the improvement of the soil quality in the orchard fields by enhancing the number and activities of microorganisms.

Development of Empirical Models for the Estimation of CBR Value of Soil from Their Index Properties: A Case Study of the Ogbia-Nembe Road in Niger Delta Region of Nigeria

This study developed empirical-mathematical models to predict the California Bearing Ratio (CBR) using soil index properties in Ogbia-Nembe road in the Niger Delta region of Nigeria. The determination of CBR of soil is a laborious operation that requires a longer time and materials leading to increased cost and schedule;this can be reduced by adopting an empirical-mathematical model that can predict the CBR using other simpler soil index properties such as Plastic Limit (PL), the Liquid Limit (LL), the Plasticity Index (PI) and the Moisture Content (MC), which are less laborious and take lesser time to obtain. Thirteen models were developed to understand the relationship between these soil index properties: the independent variable and the California Bearing Ratio (CBR): the dependent variable;Six linear, Six quadratic and One multiple linear regression models were developed for this relationship. Analysis of variance (ANOVA) on the thirteen models showed that the Optimum Moisture Content (OMC) and the Maximum Dry Density (MDD) are better independent variables for the prediction of the CBR value of Ogbia-Nembe soil generating a quadratic model and a multiple linear regression model having a better coefficient of determination R2 = 0.96 and 0.94 respectively, mean square error (MSE) of 0.74 and 1.152 respectively with Root mean square errors of 0.861 and 1.073 accordingly. These models were used to predict the CBR of the soil. The CBR values predicted by the model were further compared with those of the actual experimental test and found to be relatively consistent with minimal variance. This establishes that CBR of any soil can be predicted from the Index Property of the soil and this is more economical and takes lesser time and can be universally adopted for soil investigation.

Evaluation of Soil Fertility Quality and Environmental Driving Factors in Different Soil Types of Artificial Forests

The aim was to clarify the environmental driving factors of soil fertility indicators in artificial forests of Guangxi and comprehensively evaluate the soil fertility level.By collecting data on the current status of soil in artificial forests,the spatial distribution of major soil fertility indicators was analyzed,and the distribution map of the fertility index of artificial forests in the entire region and the comprehensive fertility index of artificial forests of different soil types were obtained.Canonical correspondence analysis method was used to analyze soil fertility indicators and environmental factors,and the environmental driving factors of soil fertility indicators for artificial forests of the main soil types in Guangxi were obtained.The results showed that over 90%of the soil fertility index of artificial forests in the entire region was between 0.20 and 0.50.The order of soil fertility index of different soil types of artificial forests from high to low was yellow brown soil>yellow red soil>yellow soil>red soil>limestone soil>latosolic red soil>laterite.In artificial forests of latosolic red soil,the correlation between soil alkaline nitrogen and organic matter,annual average temperature was high,while the correlation between soil available phosphorus and organic matter,pH was high,and the correlation between soil available potassium and environmental factors such as slope,altitude,rainfall,accumulated temperature,and slope aspect was high.In artificial forests of red soil,the correlation between soil alkaline nitrogen and slope,altitude was high,while the correlation between soil available phosphorus and accumulated temperature,rainfall was high,and the correlation between soil available potassium and pH was high.In artificial forests of limestone soil,there was a high correlation between soil alkaline nitrogen and slope,organic matter,a high correlation between soil available phosphorus and accumulated temperature,rainfall,and a high correlation between soil available potassium and pH.

Monitoring Perennial Sub-Surface Waterlogged Croplands Based on MODIS in Jianghan Plain, Middle Reaches of the Yangtze River

Perennial waterlogged soil（PWS） is induced by the high level of groundwater, and has a persistent impact on natural ecosystems and agricultural production. Traditionally, distribution information regarding PWS is mainly collected from in situ measurements through groundwater level surveys and physicochemical property analyses. However, in situ measurements of PWS are costly and time-consuming, only rough estimates of PWS areas are available in some regions. In this paper, we developed a method to monitor the perennial waterlogged cropland using time-series moderate resolution imaging spectroradiometer（MODIS） data. The Jianghan Plain, a floodplain located in the middle reaches of the Yangtze River, was selected as the study area. Temporal variations of the enhanced vegetation index（EVI）, night land surface temperature（LST）, diurnal LST differences（ΔLST）, albedo, and the apparent thermal inertia（ATI） were used to analyze the ecological and thermodynamic characteristics of the waterlogged croplands. To obtain pure remote sensing signatures of the waterlogged cropland from mixed pixels, the croplands were classified into different types according to soil and land cover types in this paper, and a linear mixing model was developed by fitting the signatures using the multiple linear regression approach. Afterwards, another linear spectral mixing model was used to get the proportions of waterlogged croplands in each 1 km×1 km pixel. The result showed an acceptable accuracy with a root-mean-square error of 0.093. As a tentative method, the procedure described in this paper works efficiently as a method to monitor the spatial patterns of perennial sub-surface waterlogged croplands at a wide scale.

Generating soil thickness maps by means of geomorphological-empirical approach and random forest algorithm in Wanzhou County,Three Gorges Reservoir

Soil thickness,intended as depth to bedrock,is a key input parameter for many environmental models.Nevertheless,it is often difficult to obtain a reliable spatially exhaustive soil thickness map in widearea applications,and existing prediction models have been extensively applied only to test sites with shallow soil depths.This study addresses this limitation by showing the results of an application to a section of Wanzhou County(Three Gorges Reservoir Area,China),where soil thickness varies from 0 to40 m.Two different approaches were used to derive soil thickness maps:a modified version of the geomorphologically indexed soil thickness(GIST)model,purposely customized to better account for the peculiar setting of the test site,and a regression performed with a machine learning algorithm,i.e.,the random forest,combined with the geomorphological parameters of GIST(GIST-RF).Additionally,the errors of the two models were quantified,and validation with geophysical data was carried out.The results showed that the GIST model could not fully contend with the high spatial variability of soil thickness in the study area:the mean absolute error was 10.68 m with the root-mean-square error(RMSE)of 12.61 m,and the frequency distribution residuals showed a tendency toward underestimation.In contrast,GIST-RF returned a better performance with the mean absolute error of 3.52 m and RMSE of 4.56 m.The derived soil thickness map could be considered a critical fundamental input parameter for further analyses.

Calibrating partial factors for Danish railway embankments using probabilistic analyses

High costs are connected with upgrading railway embankments throughout Denmark using the partial factors for geotechnical design calibrated for general application. One way to reduce the costs is reliability-based calibration of the partial factors to a reasonable safety level taking into account the specific design situations and uncertainties relevant to railway embankments. A reliability-based design has been investigated, resulting in an optimal partial factor for the considered subsoil. With a stochastic soil model to simulate the undrained shear strength of soft soil deposits, the partial factor is calibrated using asymptotic sampling for the reliability assessment. The calibration shows that the partial factor can be reduced significantly compared to the value specified in the Danish National Annex to DS/EN 1997-1 （2007）, Eurocode 7.

Soil loss tolerance in the black soil region of Northeast China

Soil loss tolerance （/） is the maximum rate of annual soil erosion that is tolerated and still allows a high level of crop productivity to be sustained economically and indefinitely. In the black soil region of Northeast China, an empirically determined, default Tvalue of 200 （t/km2.a） is used for designing land restoration strategies for different types of soils. The ob- jective of this study was to provide a methodology to calculate a quantitative T for different black soil species. A field investigation was conducted to determine the typical soil profiles of 21 black soil species in the study area and a quantitative methodology based on a modified soil productivity index model was established to calculate the Tvalues. These values, which varied from 68 t/km2.a to 358 t/km2-a, yielded an average Tvalue of 141 t/km2.a for the 21 soil species. This is 29.5% lower than the current national standard T value. Two significant factors that influenced the T value were soil thickness and vulnerability to erosion. An acceptable reduction rate of soil productivity over a planned time period of 1% is recommended as necessary for maintaining long-term sustainable soil productivity. Compared with the cur- rently used of regional unified standard T value, the proposed method, which determines T using specific soil profile indices, has more practical implications for effective, sustainable management of soil and water conservation.

Changes of soil quality induced by different vegetation restoration in the collapsing gully erosion areas of southern China

Understanding the influence of collapsing gully management restoration on soil quality and function is essential to the protection of the regional ecological environment in the collapsing gully erosion area.The primary objective of this study was to construct soil quality index(SQI)to assess the influence of different vegetation restoration types on soil quality in collapsing gully restoration.The influence of five vegetation restoration types on soil properties was investigated by using a path analysis,a comprehensive soil quality index(SQI),and a general linear model(GLM).Vegetation restoration was shown to significantly increase the saturated hydraulic conductivity(Ks),mainly due to the effect of the physical parameters of bulk density,soil cohesion,and soil water content.Meanwhile,pH,Ks,soil organic matter(OM),and sand content were revealed as reasonable indicators to evaluate the influence of vegetation restoration on soil quality.Moreover,vegetation restoration was found to significantly improve the soil quality,with the highest SQI value for natural restoration mixed forest(NF),followed by replanted arboreal forest(RA)and replanted scrubland(RS),which were all significantly higher than the SQI value of the erosion area(EA)in the collapsing gully.Additionally,vegetation type explained the most substantial proportion of total variability(46.41%),and restoration time showed a positive correlation with SQI.The results of this study can provide a reference for the restoration and protection of the regional ecological environment in the collapsing gully area.

Effect of shifting cultivation and fallow on soil quality index in Mokokchung district,Nagaland,India

Background:Shifting cultivation is a major agriculture practice in the Nagaland state of India.This study examines the effect of shifting cultivation and the length of the fallow period on soil quality index(SQI).Four sites were selected for the study,viz.,a shifting cultivation site(SCS),a 3-year-old fallow land(FL-3),a 7-year-old fallow land(FL-7),and a 12-year-old fallow land(FL-12).Soil parameters were recorded seasonally and SQI was calculated from the minimum data set.Results:With the increase in the fallow period,the values of conductivity,soil organic carbon,available nitrogen,available phosphorus,exchangeable potassium,moisture,clay,and cation exchange capacity of soil increased.Meanwhile,soil pH and bulk density decreased with fallow duration.The additive SQI_(a)values were in the order SCS<FL-3<FL-12<FL-7;meanwhile,the weighted SQI_(w)values were in the order SCS<FL-3<FL-7<FL-12.It is also observed that the SQI value decreases with the increase in soil depth under both the weighted and additive indexes.SCS with the lowest SQI value reflects the reduced soil organic carbon(SOC)and macronutrients.Increased SOC levels in site FL-12(2.88–3.94%)may be one reason for its higher SQI value.Conclusions:Our study highlights that unsustainable practices of shifting cultivation and reduction in the fallow period negatively affect soil quality.Furthermore,the study also recommends the use of the weighted method of SQI as it agrees with the reports of land use causing alteration in the soil quality.Our findings may be utilized to quickly access and disseminate information to the stakeholders and aid in constructing local soil quality index maps of the region.There is an urgent need for a rapid,cost and resource-efficient soil quality assessment and SQI may be one tool that achieves this goal.

Understanding the spatial distribution of hydrologic sensitive areas in the landscape using soil topographic index approach

Maintaining healthy watershed is pivotal to ensure sustainability in water resources thereby improving the carrying capacity of the earth.Understanding and identifying the spatial variability of hydrologically sensitive areas(HSAs)in a watershed is an important step to prioritizing the landscape to maintain water sustainability with limited resources.A spatial technique known as Soil Topographic Index(STI)was used to identify HSAs in the landscape.This study was conducted in Clinton and Tewksbury Townships in New Jersey,United States.Three different scenarios(STI>=9,STI>=10,and STI>=11)were conducted to understand the spatial distribution of HSAs in the watershed.The following conclusions were derived from this study.Firstly,a more detail representation of HSAs in the watershed was observed when applying the STI technique with a fine scale light detection and ranging(LiDAR)digitial elevation model.Secondly,all three scenarios consistently identified perennial stream corridors as HSAs;therefore,it is important to protect perennial stream corridors through implementation of various land use controls.Thirdly,this study analyzes the land use pattern of HSAs under the three scenarios and identifies the HSAs for high intensity land uses such as agriculture and urban to be the high priority locations for implementing best management practices for water quality improvements.The procedures developed in this study can be applied to watersheds in other parts of the world with similar physiographic characteristics.

Generating soil salinity, soil moisture, soil pH from satellite imagery and its analysis

In an agricultural field,the water content and salt content are defined as soil moisture and soil salinity and have to be estimated precisely.The changing of these two factors can be assessed using remote sensing technology.This study was conducted by analysing the Landsat 8 satellite images,soil data of field surveys,laboratory analyses and statistical computations.Soil properties such as soil moisture and soil salinity were estimated using soil moisture index(SMI)and soil salinity index(SSI),respectively.The research combined and integrated the soil data from survey and laboratory with Landsat 8 satellite images to build two multiple regression equations model named the soil pH Index(SpHI).They are based on bare soil and paddy leaf models as the explanatory factors of soil moisture and soil salinity changes.All the computation processes were replicated three times using three different dates of Landsat 8 satellite images to produce the multi-temporal analysis.Soil moisture increased after 30 days,while the salt content was only trace amounts.Both proposed models detected 4.49–7.59 of soil pH,4.66 in bare soil model and 6.62 in paddy leaf model.During the planting period,the soil pH in bare soil model decreased to 2.12–6.47 while the paddy leaf model increased to 4.49–7.59 with RMSE 1.40 and PRMSE 24%of accuracy.The spatial relationship between soil pH,soil salinity and soil moisture are linear but varied in correlation level from weak,moderate to strong.Based on the bare soil model,the relationship between soil pH and soil moisture shows a weak negative relationship with R28.37%and a strong positive relationship with R281.94%in paddy area and bare soil area respectively,as like as in paddy area based on the paddy leaf model with R2100%.The relationship between soil temperature and soil pH shows a weak negative relationship for all models and a moderate negative relationship of soil salinity and soil pH in bare soil area based on the bare soil model with R234.89%.

How profitable is switchgrass in Illinois, USA? An economic definition of marginal land

Background:Decisions regarding the conversion of land from an existing crop to bioenergy crops are critical for the sustainable production of both food and fuels.This study seeks to establish criteria for delineating land as“economically marginal”,and thus suited for growing switchgrass.Methods:In this case study of an Illinois agricultural field,the profitability of switchgrass,with farmgate prices of$44 Mg−1,$66 Mg−1,or$88 Mg−1,was compared to corn and soybean crop prices.Further,the study also evaluates the profitability of switchgrass when replacing corn‐based yield estimates from the Soil Productivity Index(SPI)of Illinois.Results:Based on a dry‐matter yield of 10.45 Mg ha−1,switchgrass can compete with soybeans only at the high price of$88 Mg−1,but depending on location,can compete with corn at$66 Mg−1.Across Illinois,at$88 ha−1,all Illinois land with SPI<100%and 95%of land under SPI class C(SPI 100–116)is profitable under switchgrass.Switchgrass may not be profitable relative to corn grown in the SPI class A(SPI>133)and only 7%of class B(SPI 117–132).Conclusions:Our results show that land with drainage and erosion limitations is economically marginal when corn and soybean yields are low,and the farmgate price for switchgrass is greater than$66 Mg−1.However,this may not be possible on land where switchgrass is replacing frequent soybean rotations(corn–soybean ratio≤1).Land used to produce only soybeans may only be marginal at the farmgate price of$88 Mg−1.Further studies need to be conducted to identify how much land can be converted to switchgrass without harming corn production.