Experimental investigation into the salinity effect on the physicomechanical properties of carbonate saline soil

For engineering structures with saline soil as a filling material,such as channel slope,road subgrade,etc.,the rich soluble salt in the soil is an important potential factor affecting their safety performance.This study examines the Atterberg limits,shear strength,and compressibility of carbonate saline soil samples with different NaHCO3 contents in Northeast China.The mechanism underlying the influence of salt content on soil macroscopic properties was investigated based on a volumetric flask test,a mercury intrusion porosimetry(MIP)test,and a scanning electron microscopic(SEM)test.The results demonstrated that when NaHCO3 contents were lower than the threshold value of 1.5%,the bound water film adsorbed on the surface of clay particles thickened continuously,and correspondingly,the Atterberg limits and plasticity index increased rapidly as the increase of sodium ion content.Meanwhile,the bonding force between particles was weakened,the dispersion of large aggregates was enhanced,and the soil structure became looser.Macroscopically,the compressibility increased and the shear strength(mainly cohesion)decreased by 28.64%.However,when the NaHCO3 content exceeded the threshold value of 1.5%,the salt gradually approached solubility and filled the pores between particles in the form of crystals,resulting in a decrease in soil porosity.The cementation effect generated by salt crystals increased the bonding force between soil particles,leading to a decrease in plasticity index and an improvement in soil mechanical properties.Moreover,this work provides valuable suggestions and theoretical guidance for the scientific utilization of carbonate saline soil in backfill engineering projects.

Effect of Different K^+/Mg^(2+) Ration Nutrient Solutions on Soil Salinity

Using simulated soil column experiments, the effects of different dosages and ratios of KCI and MgCI2 mixture on salinization nutrient ions in the secondary salinization soil which had 3 years of planting were studied, with the aim to provide the theory basis for the remediation of secondary salinization soil. Results showed that the content of soil K-, Mg2＋, CI- and the total salinity were increased, with the increasing concentrations of nutrient solution, while Na＋, Ca2＋ and HCO3- contents were reduced. Compared with originals oil, soil K＋, Na＋, Ca2＋, Mg2＋, CI- and total soil salinity were decreased, and HCO3- and SO42 were increased. In terms of the variation of soil total charge, the change ranges in 1：1 treatment varied small, but the residual of soil cationic decreased with increasing application of K＋ in the 2：1 treatment. It could be concluded that balanced and low application fertilizer could alleviate the soil saline, decrease the soil nutrition leaching and improve the balance among ions, while excess fertilization could accelerate the imbalance of zwitterions.

Calibration of Soil Electromagnetic Conductivity in Inverted Salinity Profiles with an Integration Method

Various calibration methods have been propounded to determine profiles of apparent bulk soil electrical conductivity (ECa) and soil electrical conductivity of a saturated soil paste extract (ECe) or a 1:5 soil water extract (EC1:5) using an electromagnetic induction instrument (EM38). The modeled coefficients, one of the successful and classical methods hitherto, were chosen to calibrate the EM38 measurements of the inverted salinity profiles of characteristic coastal saline soils at selected sites of Xincao Farm, Jiangsu Province, China. However, this method required three parameters for each depth layer. An integration approach, based on an exponential decay profile model, was proposed and the model was fitted to all the calibration sites. The obtained model can then be used to predict EC1:5 at a certain depth from electromagnetic measurements made using the EM38 device positioned in horizontal and vertical positions at the soil surface. This exponential decay model predicted the EC1:5 well according to the results of a one-way analysis of variance, and the further comparison indicated that the modeled coefficients appeared to be slightly superior to, but not statistically different from, this exponential decay model. Nevertheless, this exponential decay model was more significant and practical because it depended on less empirical parameters and could be used to perform point predictions of EC1:5 continuously with depth.

Detecting soil salinity with arid fraction integrated index and salinity index in feature space using Landsat TM imagery

Modeling soil salinity in an arid salt-affected ecosystem is a difficult task when using remote sensing data because of the complicated soil context （vegetation cover, moisture, surface roughness, and organic matter） and the weak spectral features of salinized soil. Therefore, an index such as the salinity index （SI） that only uses soil spectra may not detect soil salinity effectively and quantitatively. The use of vegetation reflectance as an indirect indicator can avoid limitations associated with the direct use of soil reflectance. The normalized difference vegetation index （NDVI）, as the most common vegetation index, was found to be responsive to salinity but may not be available for retrieving sparse vegetation due to its sensitivity to background soil in arid areas. Therefore, the arid fraction integrated index （AFⅡ） was created as supported by the spectral mixture analysis （SMA）, which is more appropriate for analyzing variations in vegetation cover （particularly halophytes） than NDVI in the study area. Using soil and vegetation separately for detecting salinity perhaps is not feasible. Then, we developed a new and operational model, the soil salinity detecting model （SDM） that combines AFⅡ and SI to quantitatively estimate the salt content in the surface soil. SDMs, including SDM1 and SDM2, were constructed through analyzing the spatial characteristics of soils with different salinization degree by integrating AFⅡ and SI using a scatterplot. The SDMs were then compared to the combined spectral response index （COSRI） from field measurements with respect to the soil salt content. The results indicate that the SDM values are highly correlated with soil salinity, in contrast to the performance of COSRI. Strong exponential relationships were observed between soil salinity and SDMs （R2〉0.86, RMSE〈6.86） compared to COSRI （R2=0.71, RMSE=16.21）. These results suggest that the feature space related to biophysical properties combined with AFII and SI can effectively provide information on soil salinity.

Effects of emitter discharge rates on soil salinity distribution and cotton(Gossypium hirsutum L.) yield under drip irrigation with plastic mulch in an arid region of Northwest China

A field experiment was carried out to investigate the effects of different emitter discharge rates under drip irrigation on soil salinity distribution and cotton yield in an extreme arid region of Tarim River catchment in Northwest China. Four treatments of emitter discharge rates, i.e. 1.8, 2.2, 2.6 and 3.2 L/h, were designed under drip irrigation with plastic mulch in this paper. The salt distribution in the range of 70-cm horizontal distance and 100-cm vertical distance from the emitter was measured and analyzed during the cotton growing season. The soil salinity is expressed in terms of electrical conductivity （dS/m） of the saturated soil extract （ECe）, which was measured using Time Domain Reflector （TDR） 20 times a year, including 5 irrigation events and 4 measured times before/after an irrigation event. All the treatments were repeated 3 times. The groundwater depth was observed by SEBA MDS Dipper 3 automatically at three experimental sites. The results showed that the order of reduction in averaged soil salinity was 2.6 L/h 〉 2.2 L/h 〉 1.8 L/h 〉 3.2 L/h after the completion of irrigation for the 3-year cotton growing season. Therefore, the choice of emitter discharge rate is considerably important in arid silt loam. Usually, the ideal emitter discharge rate is 2.4-3.0 L/h for soil desalinization with plastic mulch, which is advisable mainly because of the favorable salt leaching of silt loam and the climatic conditions in the studied arid area. Maximum cotton yield was achieved at the emitter discharge rate of 2.6 L/h under drip irrigation with plastic mulch in silty soil at the study site. Hence, the emitter discharge rate of 2.6 L/h is recommended for drip irrigation with plastiic mulch applied in silty soil in arid regions.

Spatio-Temporal Changes of Soil Salinity in Arid Areas of South Xinjiang Using Electromagnetic Induction

The aim of this paper was to research the spatio-temporal changes in total soluble salt content （TS） in a typical arid region of South Xinjiang, China, where the climate is arid and soil salinization happens easily. The total soluble salt content was interpreted by measurements made in the horizontal mode with EM38 and EM31. The electromagnetic induction （EM） surveys were made three times with the apparent soil electrical conductivity （ECa） measurements taken at 3 873 locations in Nov. 2008, 4 807 locations in Apr. 2009 and 6 324 locations in Nov. 2009, respectively. For interpreting the ECa measurements into total soluble salt content, calibtion sites were needed for EM survey of each time, e.g., 66 sites were selected in Nov. 2008 to measure ECa, and soils-core samples were taken by different depth layers of 0-10, 10-20 and 20-40 cm at the same time. On every time duplicate samples were taken at five sites to allevaite the local-scale variability, and soil temperatures in different layers through the profiles were also measured. Factors including TS, pH, water content, bulk density were analyzed by lab experiments. ECa calibration equations were obtained by linear regression analysis, which indicated that soil salinity was one primary concern to ECa with a determination coefficient of 0.792 in 0-10 cm layer, 0.711 in 10-20 cm layer and 0.544 in 20-40 cm layer, respectively. The maps of spatial distribution were predicted by Kriging interpolation, which showed that the high soil salinity was located near the drainage canal, which validated the trend effect caused by the irrigation canal and the drainage canal. And by comparing the soil salinity in different layers, the soluble salt accumulated to the top soil surface only in the area where the soil salinization was serious, and in the other areas, the soil salinity trended to increase from the top soil surface to 40 cm depth. Temporal changes showed that the soil salinity in November was higher than that in April, and the soil salinization trended to aggravate, especially in the top soil layer of 0-10 cm.

Spatio-temporal variations of soil water content and salinity around individual Tamarix ramosissima in a semi-arid saline region of the upper Yellow River, Northwest China

Ecological restoration by Taman＇x plants on semi-arid saline lands affects the accumulation, distribution patterns and related mechanisms of soil water content and salinity. In this study, spatio-temporal variations of soil water content and salinity around natural individual Tamarix ramosissiraa Ledeb. were invetigated in a semi-arid saline region of the upper Yellow River, Northwest China. Specifically, soil water content, electrical conductivity （EC）, sodium adsorption ratio （SARa）, and salt ions （including Na＋, K＋, Ca2＋, Mg2＋ and 8042-） were measured at different soil depths and at different distances from the trunk of T. ramasissima in May, July, and September 2016. The soil water content at the 20-80 cm depth was significantly lower in July and September than in May, indicating that T. ramosissima plants absorb a large amount of water through the roots during the growing period, leading to the decreasing of soil water content in the deep soil layer. At the 0-20 cm depth, there was a salt island effect around individual T. ramosissima, and the ECe differed significantly inside and outside the canopy of T. ramosissima in May and July. Salt bioaccumulation and stemflow were two major contributing factors to this difference. The SAR at the 0-20 cm depth was significantly different inside and outside the canopy of T. ramosissima in the three sampling months. The values of SAR~ at the 60-80 cm depth in May and July were significantly higher than those at the 0-60 cm depth and higher than that at the corresponding depth in September. The distribution of Na＋ in the soil was similar to that of the SAI, while the concentrations of K＋, Ca2＋, and Mg2＋ showed significant differences among the sampling months and soil depths. Both season and soil depth had highly significant effects on soil water content, ECe and SARa, whereas distance from the trunk of T. ramosissima only significantly affected ECe. Based on these results, we recommend co-planting of shallow-rooted salt-tolerant species near the Tamarx plants and avoiding planting herbaceous plants inside the canopy of T. ramodssima for afforestation in this semi-arid saline region. The results of this study may provide a reference for appropriate restoration in the semi-arid saline regions of the upper Yellow River.

Effects of soil salinity on rhizosphere soil microbes in transgenic Bt cotton fields

With increased cultivation of transgenic Bacillus thuringiensis （Bt） cotton in the saline alkaline soil of China, assessments of transgenic crop biosafety have focused on the effects of soil salinity on rhizosphere microbes and Bt protein residues. In 2013 and 2014, investigations were conducted on the rhizosphere microbial biomass, soil enzyme activities and Bt protein contents of the soil under transgenic Bt cotton （variety GK19） and its parental non-transgenic cotton （Simian 3） cultivated at various salinity levels （1.15, 6.00 and 11.46 dS m-1）. Under soil salinity stress, trace amounts of Bt proteins were ob- served in the Bt cotton GK19 rhizosphere soil, although the protein content increased with cotton growth and increased soil salinity levels. The populations of slight halophilic bacteria, phosphate solubilizing bacteria, ammonifying bacteria, nitrifying bacteria and denitrifying bacteria decreased with increased soil salinity in the Bt and non-Bt cotton rhizosphere soil, and the microbial biomass carbon, microbial respiration and soil catalase, urease and alkaline phosphatase activity also decreased. Correlation analyses showed that the increased Bt protein content in the Bt cotton rhizosphere soil may have been caused by the slower decomposition of soil microorganisms, which suggests that salinity was the main factor influencing the relevant activities of the soil microorganisms and indicates that Bt proteins had no clear adverse effects on the soil microorganisms. The results of this study may provide a theoretical basis for risk assessments of genetically modified cotton in saline alkaline soil.

Improved Prediction and Reduction of Sampling Density for Soil Salinity by Different Geostatistical Methods

The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.

Effect of Initial Soluble Salt Composition of Saline Soil on Salinity Tolerance of Barley Plant

A pot experiment was carried out on a marine saline soil to study the effect of initial soluble Na/Ca ratio of saline soil on the salinity tolerance of barley plant.The results showed that (1) the Na/Ca ratio affected significantly the dry weight of the plant at an earlier stage of growth,the critical values of initial Na/Ca ratio at which the plant could grow normally on soils containing salts of 2.5,3.5 and 4.5g kg^-1 were 30,20 and 15,respectively;(2)smaller Na/Ca ratio resulted in a considerable decrease in Na accumulation but a great increase in K accumulation in the barley plant;and (3) the plasmallema of barley leaf were badly injured when the Na/Ca ratio was more than 30 and the increase of Na content of plant caused an exudation of K from the leaf cells.Some critical indexes were suggested for the cultivation of barley plant on marine saline soils and could be used as reference in the biological reclamation of marine saline soils.

Mapping Soil Salinity Using a Similarity-based Prediction Approach:A Case Study in Huanghe River Delta,China

Spatial distribution of soil salinity can be estimated based on its environmental factors because soil salinity is strongly affected and indicated by environmental factors. Different with other properties such as soil texture, soil salinity varies with short-term time. Thus, how to choose powerful environmental predictors is especially important for soil salinity. This paper presents a similarity-based prediction approach to map soil salinity and detects powerful environmental predictors for the Huanghe(Yellow) River Delta area in China. The similarity-based approach predicts the soil salinities of unsampled locations based on the environmental similarity between unsampled and sampled locations. A dataset of 92 points with salt data at depth of 30–40 cm was divided into two subsets for prediction and validation. Topographical parameters, soil textures, distances to irrigation channels and to the coastline, land surface temperature from Moderate Resolution Imaging Spectroradiometer(MODIS), Normalized Difference Vegetation Indices(NDVIs) and land surface reflectance data from Landsat Thematic Mapper(TM) imagery were generated. The similarity-based prediction approach was applied on several combinations of different environmental factors. Based on three evaluation indices including the correlation coefficient(CC) between observed and predicted values, the mean absolute error and the root mean squared error we found that elevation, distance to irrigation channels, soil texture, night land surface temperature, NDVI, and land surface reflectance Band 5 are the optimal combination for mapping soil salinity at the 30–40 cm depth in the study area(with a CC value of 0.69 and a root mean squared error value of 0.38). Our results indicated that the similarity-based prediction approach could be a vital alternative to other methods for mapping soil salinity, especially for area with limited observation data and could be used to monitor soil salinity distributions in the future.

Spatial prediction and modeling of soil salinity using simple cokriging, artificial neural networks, and support vector machines in El Outaya plain, Biskra, southeastern Algeria

Soil salinization is one of the most predominant environmental hazards responsible for agricultural land degradation,especially in the arid and semi-arid regions.An accurate spatial prediction and modeling of soil salinity in agricultural land are so important for farmers and decision-makers to develop the appropriate mechanisms to prevent the loss of fertile soil and increase crop production.El Outaya plain is marked by soil salinity increases due to the excessive use of poor groundwater quality for irrigation.This study aims to compare the performance of simple kriging,cokriging(SCOK),multilayer perceptron neural networks(MLP-NN),and support vector machines(SVM)in the prediction of topsoil and subsoil salinity.The field covariates including geochemical properties of irrigation groundwater and physical properties of soil and environmental covariates including digital elevation model and remote sensing derivatives were used as input candidates to SCOK,MLP-NN,and SVM.The optimal input combination was determined using multiple linear stepwise regression(MLSR).The results revealed that the SCOK using field covariates including water electrical conductivity(ECw)and sand percentage(sand%),and environmental covariates including land surface temperature(LST),topographic wetness index(TWI),and elevation could significantly increase the accuracy of soil salinity spatial prediction.The comparison of the prediction accuracy of the different modeling techniques using the Taylor diagram indicated that MLP-NN using LST,TWI,and elevation as inputs were more accurate in predicting the topsoil salinity[ECs(TS)]with a mean absolute error(MAE)of 0.43,root mean square error(RMSE)of 0.6 and correlation coefficient of 0.946.MLP-NN using ECw and sand%as inputs were more accurate in predicting the subsoil salinity[ECs(SS)]with MAE of 0.38,RMSE of0.6,and R of 0.968.

Distribution Characteristics of Soil Salinity in Absorbing Carbon Forest

[Objective] The paper was to analyze the soil salinity characteristics in Xinjiang region, and develop salinization characteristic research, so as to provide reference for salinization research in arid region. [Method] With different land types of soil vertical profiles in Karamay absorbing carbon forest as research object, soil salinity and water soluble ions were determined and analyzed using statistical characteristic value and trend surface, and the distribution characteristic of soil salinity in the region was explored.[Result] The salinity in survey area of absorbing carbon forest mainly were sulfate-chloride type and chloride type, of which cations were mainly Na＋, K＋ and Ca2＋, anions were CO32-, Cl- and SO42-, the variation coefficient of CO32 - was as high as 292.91, while the variation coefficient of Cl- was 265.56. The variation of soil total soluble salts in the soil layer of 0-100 cm was not significant, indicating that the content in each soil layer was relatively stable. [Conclusion] The study provided basis for speeding up dynamic monitoring for soil salinization and finding the effective control approach against salinization

Influence of Plant Growth Promoting Rhizobacterial Inoculation on Wheat Productivity Under Soil Salinity Stress

Soil salinity affects the growth and yield of crops.The stress of soil salinity on plants can be mitigated by inoculation of plant growth promoting bacteria(PGPR).The influence of PGPR inoculation on wheat(Triticum aestivum L.)crop productivity under salinity stress has not been properly addressed so far.Therefore,the present study was conducted to investigate the effects of various PGPR strains(W14,W10 and 6K;alone and combined)at several growth attributes of wheat plant under different soil salinity gradients(3,6 and 9 dS m-1).The growth attributes of wheat(height,roots,shoots,spikes,grains quality,biological and economical yield,nutrients nitrogen,phosphorus and potassium in grains)were highly affected by salinity and decreased with increasing salinity level.The PGPR inoculation substantially promoted growth attributes of wheat and prominent results were observed in W14×W10×6K treatment at all salinity levels.The results suggest that inoculation of PGPR is a potential strategy to mitigate salinity stress for improving wheat growth and yield.

The Effects of the Chemical Components of Soil Salinity on Electrical Conductivity in the Region of the Delta Oasis of Weigan and Kuqa Rivers,China

In order to assess the effects of chemical properties of soil salinity on electrical conductivity of 1：5 soil/water extract （EC1：5）, the study focused on revealing the main chemical factors contributing to EC of soil extracts and their relative importance. The relationship between EC1：5 and the chemical properties of soil salinity in the delta oasis of Weigan and Kuqa rivers, China, were studied using path coefficient analysis, a path analysis method. We studied each key element affecting EC1：5 either directly or indirectly. The results obtained show that the salt content, total dissolved solids （TDS）, and the sum of the sodium ion concentration and the kalium ion concentration are the most influential factors on 1：5 soil/ water extract （EC1：5） in the 0-10 cm and the 30-50 cm soil layer. The results show that the sequence of direct path coefficients in the 0-10 cm and the 30-50 cm soil layers on soil conductivity is TDS→Na^＋ ＋ K^＋→Salt content→Ca^2＋→Cl-→the sodium dianion ratio （SDR）→pH→ SO4^2-→HCO3^-→Mg^2＋→the soluble sodium percentage （SSP） sodium absorption ratio （SAR） and TDS→Salt content→Na^＋ ＋ K^＋→Ca^2＋→SDR→Mg^2＋→HCO3^-→SSP→pH→SO4^2-→SAR→Cl^-. The salt content, chlorine ion, and SAR are the main factors affecting 1：5 soil/water extract （EC1：5） in the 10-30 centimeter soil layer. The order of direct path coefficients result is as follows： Salt content→Cl^-→SAR→SSP→TDS→Ca^2＋→Mg^2＋= SO4^2-→HCO3^-→pH→SDR→Na^- ＋ K^＋. Moreover, the effects of HCO3^-, pH were very weak. Though the direct path coefficients between EC1：5 and SAR, SO4^2- and Ca^2＋ were not high, influence of other chemical factors caused the coefficients to increase, making the summation of their direct and indirect path coefficients relatively high. The models of the different soil layers were structured separately. Evidences showed that multiple regression relations between EC1：5 and most of the primary factors had sound reliability and very good accuracy. The research results can serve as a reference to the scientific management amelioration and utilization of saline in the Delta Oasis of Weigan and Kuqa rivers.

Effects of water application intensity of micro-sprinkler irrigation and soil salinity on environment of coastal saline soils

To achieve the greatest leaching efficiency,water movement must occur under unsaturated flow conditions.Accordingly,the water application intensity of irrigation must be chosen carefully.The aim of this study was to evaluate the impact of the water application intensity of micro-sprinkler irrigation on coastal saline soil with different salt contents.To achieve this objective,a laboratory experiment was conducted with three soil salinity treatments(2.26,10.13,and 22.29 dS/m)and three water application intensity treatments(3.05,5.19,and 7.23 mm/h).The results showed that the effect of soil salinity on soil water content,electrical conductivity,and pH was significant,and the effect of the water application intensity was insignificant.High soil water content was present in the 40e60 cm profile in all soil salinity treatments,and the content was higher in the medium and high water application intensity treatments than in the low-intensity treatment.Significant salt leaching occurred in all treatments,and the effect was stronger in the high soil salinity treatment and medium water application intensity treatment.In the medium and high soil salinity treatments,pH exhibited a decreasing trend,with no trend change in the low soil salinity treatment,and the pH value was higher in the medium water application intensity treatment than in the other two treatments.These results indicated that the three intensities evaluated had no statistically different effect on the electrical conductivity of saturated soil-paste extracts(EC)in the upper 20 cm of the soil profile,and it would be better to maintain a lower value of the water application intensity.

An analysis on the error structure and mechanism of soil moisture and ocean salinity remotely sensed sea surface salinity products

For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere（negative bias） and along the southern,northern and some other oceanic margins（positive or negative bias）.The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature（TB） reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.

Soil Salinity and Soil Water Content Estimation Using Digital Images in Coastal Field:A Case Study in Yancheng City of Jiangsu Province,China

Soil is the essential part for agricultural and environmental sciences,and soil salinity and soil water content are both the important influence factors for sustainable development of agriculture and ecological environment.Digital camera,as one of the most popular and convenient proximal sensing instruments,has its irreplaceable position for soil properties assessment.In this study,we collected 52 soil samples and photographs at the same time along the coast in Yancheng City of Jiangsu Province.We carefully analyzed the relationship between soil properties and image brightness,and found that soil salt content had higher correlation with average image brightness value than soil water content.From the brightness levels,the high correlation coefficients between soil salt content and brightness levels concentrated on the high brightness values,and the high correlation coefficients between soil water content and brightness levels focused on the low brightness values.Different significance levels(P)determined different brightness levels related to soil properties,hence P value setting can be an optional way to select brightness levels as the input variables for modeling soil properties.Given these information,random forest algorithm was applied to develop soil salt content and soil water content inversion models using randomly 70%of the dataset,and the rest data for testing models.The results showed that soil salt content model had high accuracy(R_(v)^(2)=0.79,RMSE_(v)=12 g/kg,and RPD_(v)=2.18),and soil water content inversion model was barely satisfied(R_(v)^(2)=0.47,RMSE_(v)=3.04%,and RPD_(v)=1.38).This study proposes a method of modeling soil properties with a digital camera.Combining unmanned aerial vehicle(UAV),it has potential popularization and application value for precise agriculture and land management.

Integrating multiple electromagnetic data to map spatiotemporal variability of soil salinity in Kairouan region, Central Tunisia

Soil salinization is a major problem affecting soils and threatening agricultural sustainability in arid and semi-arid regions,which makes it necessary to establish an efficient strategy to manage soil salinity and confront economic challenges that arise from it.Saline soil recovery involving drainage of shallow saline groundwater and the removal of soil salts by natural rainfall or by irrigation are good strategies for the reclamation of salty soil.To develop suitable management strategies for salty soil reclamation,it is essential to improve soil salinity assessment pro cess/mechanism and to adopt new approaches and techniques.T his study mapped a recovered area of 7200 m2 to assess and verify variations in soil salinity in space and time in K airouan region in Central Tunisia,taking into account the thickness of soil materials.Two electromagnetic conductivity meters(EM38 and EM31)were used to measure the electrical conductivity of saturated soil-paste extract(ECe)and apparent electrical conductivity(E Ca).Multiple linear regression was established between ECe and ECa,and it was revealed that ECa-EM38 is optimal for E Ce prediction in the surface soils.Salinity maps demonstrated that the spatial structure of soil salinity in the region of interest was relatively unchanged but varied temporally.Variation in salinity at the soil surface was greater than that at a depth.These findings can not only be used to track soil salinity variations and their significance in the field but also help to identify the spatial and temporal features of soil salinity,thus improving the efficiency of soil management.

Geostatistical analysis of variations in soil salinity in a typical irrigation area in Xinjiang, northwest China

Characterizing spatial and temporal variability of soil salinity is tremendously important for a variety of agronomic and environmental concerns in arid irrigation areas. This paper reviews the characteristics and spatial and temporal variations of soil salinization in the Ili River Irrigation Area by applying a geostatistical approach. Results showed that: (1) the soil salinity varied widely, with maximum value of 28.10 g/kg and minimum value of 0.10 g/kg, and was distributed mainly at the surface soil layer. Anions were mainly SO42- and Cl-, while cations were mainly Na+ and Ca2+; (2) the abundance of salinity of the root zone soil layer for different land use types was in the following order: grassland > cropland > forestland. The abundance of salinity of root zone soil layers for different periods was in the following order: March > June > September; (3) the spherical model was the most suitable variogram model to describe the salinity of the 0-3 cm and 3-20 cm soil layers in March and June, and the 3-20 cm soil layer in September, while the exponential model was the most suitable variogram model to describe the salinity of the 0-3 cm soil layer in September. Relatively strong spatial and temporal structure existed for soil salinity due to lower nugget effects; and (4) the maps of kriged soil salinity showed that higher soil salinity was distributed in the central parts of the study area and lower soil salinity was distributed in the marginal parts. Soil salinity tended to increase from the marginal parts to the central parts across the study area. Applying the kriging method is very helpful in detecting the problematic areas and is a good tool for soil resources management. Managing efforts on the appropriate use of soil and water resources in such areas is very important for sustainable agriculture, and more attention should be paid to these areas to prevent future problems.