Reclamation of Coastal Soil Salinity towards Sustainable Rice Production and Mitigating Global Warming Potentials in the Changing Climate

Soil salinity has become a major constraint to rice productivity in the coastal region of Bangladesh, which threatened food security. Therefore, field experiment was conducted at salt stressed Shyamnagor Upazilla of Satkhira district to improve the soil salinity status, sustainable rice production and suppression of global warming potentials. Selected soil amendments viz. trichocompost, tea waste compost, azolla compost and phospho-gypsum (PG) were applied in the field plots one week prior to rice transplanting. In addition, proline solution (25 mM) was applied on the transplanted rice plants at active vegetative stage. Gas samples from the paddy field were collected by Closed Chamber technique and analyzed in by Gas Chromatograph. The 25% replacement of chemical fertilizer (i.e., 75% NPKS) with trichocompost, tea waste compost, Azolla compost and Phospho-gypsum amendments increased grain yield by 4.7% - 7.0%, 2.3% - 7.1% 11.9% - 16.6% and 9.5% - 14.2% during dry boro rice cultivation, while grain yield increments of 5.0% - 7.6%, 2.3% - 10.2%, 12.8% - 15.3% and 10.2% - 15.3% were recorded in wet Aman season respectively, compared to chemically fertilized (100% NPKS) field plot. The least GWPs 3575 and 3650 kg CO2 eq./ha were found in PG Cyanobacterial mixture with proline (T10) and tea waste compost with proline (T8) amended rice field, while the maximum GWPs 4725 and 4500 kg CO2 eq./ha were recorded in NPKS fertilized (100%, T2) and NPKS (75%) with Azolla compost (T5) amended plots during dry boro rice cultivation. The overall soil properties improved significantly with the selected soil amendments, while soil electrical conductivity (EC), soil pH and Na+ cation in the amended soil decreased, eventually improved the soil salinity status. Conclusively, phospho-gypsum amendments with cyanobacteria inoculation and proline solution (25 mM) application could be an effective option to reclaim coastal saline soils, sustaining rice productivity and reducing global warming potentials.

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.

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.

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.

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.

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.

Quantitative Evaluation and Uncertainty Assessment on Geostatistical Simulation of Soil Salinity Using Electromagnetic Induction Technique

Diagnosis of soil salinity and characterizing its spatial variability both vertically and horizontally are needed to establish control measures in irrigated agriculture. In this regard, it is essential that salinity development in varying soil depths be known temporally and spatially. Apparent soil electrical conductivity, measured by electromagnetic induction instruments, has been widely used as an auxiliary variable to estimate spatial distribution of field soil salinity. The main objectives of this paper were adopted a mobile electromagnetic induction (EMI) system to perform field electromagnetic (EM) survey in different soil layers, to evaluate the uncertainty through Inverse Distance Weighted (IDW) and Ordinary Kriging (OK) methods, and to determine which algorithm is more reliable for the local and spatial uncertainty assessment. Results showed that EM38 data from apparent soil electrical conductivity are highly correlated with salinity, more accurate for estimating salinity from multiple linear regression models, which the correlation coefficient of 0 - 20, 20 - 40, 40 - 60 and 60 - 80 cm were 0.9090, 0.9228, 0.896 and 0.9085 respectively. The comparison showed that the prediction accuracy of two methods also displays good performance for soil salinity, the estimation precision of IDW method (with E = 0.8873, 0.9075, 0.8483 and 0.901, RPD = 9.64, 8.01, 8.17 and 11.23 in 0 - 20, 20 - 40. 40 - 60 and 60 - 80 cm soil layers, respectively) was superior to that of OK (with E = 0.8857, 0.872, 0.8744 and 0.8822, RPD = 9.44, 7.83, 8.52 and 10.88, respectively), but differences of two methods in predictions are not significant. The obtained salinity map was helpful to display the spatial patterns of soil salinity and monitor and evaluate the management of salinity.

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.

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.

Effects of Soil Salinity on Microbial Biomass Nitrogen of Landscape Soil

Soil salinization can limit the development of agriculture in the Yellow River Delta.In this paper,saline and alkaline farmland in the Yellow River Delta was chosen as the research object,and effects of soil salinity on soil microbial biomass nitrogen(SMBN) under different conditions were investigated to study the response of soil nitrogen turnover to salt stress.There were four salinity gradients(S1:0.1%;S2:0.5%;S3:0.9%;S4:1.3%),and four substrates were added to the soil.The results showed that after the addition of various substrates,SMBN in treatments with high soil salinity(S3 and S4) was obviously lower than that in treatments with low soil salinity(S1 and S2).In comparison with treatment S1,the average of SMBN in treatments S3 and S4 decreased by 35.8% and 46.7% respectively when there was no substrate added to them;it declined by 55.6% and 56.1% respectively as the carbon source was added to them;it reduced by 24.6% and 28.3% when the nitrogen source was added to them;it dropped by 43.8% and 57.0% respectively as the carbon and nitrogen source were added to them.Compared with treatments without substrates,the addition of the nitrogen source could not improve SMBN;the addition of the carbon source or carbon and nitrogen source could enhance SMBN obviously,and it increased by 60.9% and 66.1%(or 110.8% and 140.2%) in treatments with low soil salinity(S1 and S2),while it changed slightly in treatments with high soil salinity(S3 and S4).In order to increase SMBN,it is needed to apply organic fertilizer or chemical fertilizer and organic fertilizer to maintain or improve soil fertility.

Soil Salinity Detection in Semi-Arid Region Using Spectral Unmixing, Remote Sensing and Ground Truth Measurements

Soil salinity is one of the serious environmental problems ravaging the soils of arid and semi-arid region, thereby affecting crop productivity, livestock, increase level of poverty and land degradation. Hyperspectral remote sensing is one of the important techniques to monitor, analyze and estimate the extent and severity of soil salt at regional to local scale. In this study we develop a model for the detection of salt-affected soils in arid and semi-arid regions and in our case it’s Ghannouch, Gabes. We used fourteen spectral indices and six spectral bands extracted from the Hyperion data. Linear Spectral Unmixing technique (LSU) was used in this study to improve the correlation between electrical conductivity and spectral indices and then improve the prediction of soil salinity as well as the reliability of the model. To build the model a multiple linear regression analysis was applied using the best correlated indices. The standard error of the estimate is about 1.57 mS/cm. The results of this study show that hyperion data is accurate and suitable for differentiating between categories of salt affected soils. The generated model can be used for management strategies in the future.

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.

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.

Mitigation Rice Yield Scaled Methane Emission and Soil Salinity Stress with Feasible Soil Amendments

Sea level rise and saline water intrusion have been affecting land use and crop production especially rice in the coastal areas of major rice growing countries including Bangladesh. The upward trend in salinity intrusion has been hampering crop production, particularly rice cultivation in the coastal areas of Bangladesh. Therefore, an experiment was conducted on rice planted saline soils under the Nethouse at Bangladesh Agricultural University, Mymensingh to improve the properties of salt affected soils for rice cultivation as well as controlling methane (CH4) emissions with feasible soil organic amendments and recommended inorganic fertilizers. The experimental treatments were arranged under 25 mM NaCl, 50 mM NaCl and 75 mM NaCl salinity levels with different combinations of NPKSZn, biochar, phosphogypsum and Trichocompost. It was found that CH4 emission rates were suppressed with phospho-gypsum and biochar amendments within the salinity level 25 mM to 50 mM, beyond this salinity level (at 75 mM), soil amendments were not effective to control CH4 emissions. From panicle initiation to grain ripening stages treatment T4 (100% NPKSZn + 75 mM NaCl stress) showed the highest CH4 emission rate, while lower CH4 emission rate was recorded in T5 (100% NPKSZn + 25 mM NaCl stress + Phospho-gypsum) and T8 treatment (100% NPKSZn + 50 mM NaCl + Phospho-gypsum). In case of seasonal total CH4 emission, Phospho-gypsum was found most effective to mitigate total CH4 emissions followed by biochar and trichocompost amendments in all salinity levels, probably due to the improved soil redox potential status (Eh), decreased electrical conductivity (EC), increased SO42-, NO3- , Mn4+ etc. in the rice rhizosphere. Rice growth and yield components were badly affected by increasing salinity levels. Phospho-gypsum, biochar and trichocompost amendments increased plant height, panicles number/hill, shoot biomass and grain yield/hill at 25 mM NaCl stress condition. However, salinity stress 50 mM to 75 mM severely affected rice growth and yield components, eventhough phospho-gypsum, biochar and trichocompost were applied. Among the amendments, phosphogypsum and biochar significantly decreased yield scaled CH4 emission (GHGI) in salinity levels 25 mM to 75 mM. After harvesting rice, the overall soil properties such as organic matter content, available P, available S, exchangeable K+ and Ca2+, K+/Na+, Ca2+/Na+ ratios etc. were increased with the biochar, phospho-gypsum and trichocompost amendments. The highest ratios of K+/Na+ and Ca+/Na+ were found in the extract of saline soil at 25 mM with phospho-gypsum amendments followed by biochar and trichocompost amendments. Furthermore, soil SO42-, NO3- , Mn4+ and Fe3+ contents in rice root rhizosphere were increased in the amended saline soils, which caused significant reduction in seasonal methane emissions. Therefore, it could be concluded that the combined application of phospho-gypsum and biochar with the recommended NPKSZn fertilizers in saline soils may be a good practice for increasing tolerance to salinity in rice by increasing K+/Na+, Ca2+/Na+ ratios, while decreasing yield scaled CH4 emission (GHGI) in salinity levels 25 mM to 75 mM.

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.

Effects of drip irrigation and cropping on soil salinity,ionic composition and waxy corn production in a severely saline and calcareous and gypsiferous soil

Drip technologies have been suggested as practical for irrigation under conditions of high salinity and for reclamation of saline soils.Drip irrigation triggered by soil water potential thresholds was applied to both reclaim a severely saline calcareous gypsiferous soil and irrigate a waxy corn crop(Zea mays L.sinesis Kulesh).However,there is a lack of knowledge on the sustainability of reclamation of saline soils with drip irrigation and the changes in soil salinity and salt ion composition during the amelioration process.Therefore,effects on soil salinity,its ionic composition,and on crop growth and yields were evaluated in an experiment conducted in the Yinchuan Plain,northwest China.Treatments included fields in their first to fourth years of the drip irrigation reclamation-cropping scheme and adjacent native,non-cropped or irrigated salinesodic land as control.Yield of waxy corn increased and days of growth to maturity decreased as a function of time and reclamation management.The improvement in crop performance could be largely credited to the reduction of soil salinity and changes in salt composition under the drip-irrigated reclamation protocols.The drip irrigation regime created a region of low salinity proximal to the emitters conducive to germination and plant growth.Deleterious ions for crop growth such as Na+and Cl^(-)were reduced while Ca2+and Mg2+concentration increased,especially in the upper 40 cm of soil.After only a single season of drip-irrigated waxy corn production,both Cl-SO_(4)^(2-)ratios and sodium adsorption ratio(SAR)decreased dramatically.The results suggested that drip irrigation is an effective technology for reclamation of severely saline-affected soils,such as those widely distributed over the Ningxia Plain in China and that this or similar reclamation strategy could be appropriate for reclamation of other hard to manage calcareous and gypsiferous soils.

Comparative investigation on soil salinity leaching under subsurface drainage and ditch drainage in Xinjiang arid region

This study was carried out to explore the effects of leaching salinity under subsurface drainage and mulched drip irrigation on saline and alkaline land from the year 2012 to 2014 in Xinjiang Region of China.Three sampled points were both set up in the subsurface drainage and ditch drainage areas.Soil samples were obtained at varied depths.Through observing the underground water table under each sampled point and measuring the electrical conductivity(EC)of the soil extracts,the following results were obtained:(1)after draining,the underground water table ranged from 1.6 m to 2.2 m in the ditch drainage area,and ranged from 1.5 m to 2.2 m in the subsurface drainage area.Thus,both irrigations could control underground water table below 1.5 m which is deeper than the main water-absorbing layers of crop root systems;(2)for subsurface drainage,the closer to the pipe,the better to leach salinity;decreased from the initial 13.54-22.95 g/kg to 8.20-11.47 g/kg;(3)compared with the amounts in 2012,soil total salt at each sampling point at depths of 0-200 cm in subsurface drainage area decreased by 42.99%,36.84%and 24.41%respectively in 2014;and in ditch drainage area decreased by 46.85%,38.12%and 30.80%respectively in 2014.The results showed both ditch and subsurface drainage could leach salinity effectively.