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 S...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 CO<sub>2</sub> 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 CO<sub>2 </sub>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.展开更多
The estuary tides affect groundwater dynamics;these areas are susceptible to waterlogging and salinity issues.A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system...The estuary tides affect groundwater dynamics;these areas are susceptible to waterlogging and salinity issues.A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system that works with solar energy and belong to a commercial farm located in Northern Sudan.To monitor soil salinity and calcium carbonate in the area and stop future degradation of soil resources,easy,non-intrusive,and practical procedures are required.The objective of this study was to use remote sensing-determined Sentinel-2 satellite imagery using various soil indices to develop prediction models for the estimation of soil electrical conductivity(EC)and soil calcium carbonate(CaCO_(3)).Geo-referenced soil samples were collected from 72 locations and analyzed in the laboratory for soil EC and CaCO_(3).The electrical conductivity of the soil saturation paste extract was represented by average values in soil dataset samples from two fields collected from the topsoil layer(0 to 15 cm)characteristic of the local salinity gradient.The various soil indices,used in this study,were calculated from the Sentinel-2 satellite imagery.The prediction was determined using the root mean square error(RMSE)and cross validation was done using coefficient of determination.The results of regression analysis showed linear relationships with significant correlation between the EC analyzed in laboratory and the salinity index-2“SI2”(Model-1:R^(2)=0.59,p=0.00019 and root mean square error(RMSE=1.32%)and the bare soil index“BSI”(Model-2:R^(2)=0.63,p=0.00012 and RMSE=6.42%).Model-1 demonstrated the best model for predicting soil EC,and validation R^(2)and RMSE values of 0.48%and 1.32%,respectively.The regression analysis results for soil CaCO_(3)determination showed linear relationships with data obtained in laboratory and the bare soil index“BSI”(Model-3:R^(2)=0.45,p=0.00021 and RMSE=1.29%)and the bare soil index“BSI”&Normalized difference salinity index“NDSI”(Model-4:R^(2)=0.53,p=0.00015 and RMSE=1.55%).The validation confirmed the Model-3 results for prediction of soil CaCO_(3)with R^(2)and RMSE values of 0.478%and 1.29%,respectively.Future soil monitoring programs might consider the use of remote sensing data for assessing soil salinity and CaCO_(3)using soil indices results generated from satellite image(i.e.,Sentinel-2).展开更多
In response to the global food crisis and the imperative to address soil degradation, the international agricultural policy is actively working to alleviate the adverse impacts of soil salinity. As part of this initia...In response to the global food crisis and the imperative to address soil degradation, the international agricultural policy is actively working to alleviate the adverse impacts of soil salinity. As part of this initiative, a field trial spanning two consecutive seasons (2019/20-2020/21) was conducted under saline conditions. The primary objective was to evaluate the influence of various compost sources, including vermicompost at a rate of 0.5 ton·fed<sup>-1</sup> and plant residues compost at a rate of 5.0 ton·fed<sup>-1</sup>, as main plots. Subplots were established by applying agricultural gypsum, both in the presence and absence of gypsum requirements. Additionally, sub-subplots were created by externally applying cobalt at a rate of 10.0 mg·L<sup>-1</sup>, with one sub-subplot receiving foliar cobalt application and the other not. The trial sought to assess the growth performance, chemical composition, enzymatic antioxidants, yield, and quality of cabbage plants (Brassica oleracea var. capitata L.) cultivated in saline soil. According to the findings, cabbage plants exhibited the most favorable response in terms of plant height, chlorophyll content, carotene levels, leaf area, nitrogen (N), phosphorus (P), potassium (K), head yield, vitamin C, and total dissolved solids (TDS) when treated with vermicompost, followed by plant compost. Conversely, plants grown without compost exhibited the least improvement in performance. Cabbage treated with agricultural gypsum requirements showed better performance than those without gypsum amendment. Moreover, plants subjected to cobalt spray demonstrated the highest growth, yield, and quality parameters compared to those without cobalt foliar application. In contrast, the control group (plants without the studied treatments) displayed the highest levels of enzymatic antioxidants, specifically catalase and peroxidase. This indicates that soil salinity stress led to an increase in catalase and peroxidase production in cabbage plants as a defense against the harmful impact of reactive oxygen species (ROS) resulting from soil salinity stress. The applied treatments (compost, gypsum, and cobalt) led to a reduction in the cabbage plant’s inherent production of catalase and peroxidase. Generally, the combined treatment of vermicompost × gypsum requirements × cobalt proved effective in mitigating the detrimental effects of soil salinity on cabbage plants. These findings hold significance for farmers and policymakers aiming to enhance agricultural productivity in regions affected by soil salinity. Additionally, further research can explore the long-term effects of these treatments on soil health and crop sustainability.展开更多
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 sal...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.展开更多
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 ae...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.展开更多
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 d...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.展开更多
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 co...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.展开更多
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 enviro...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.展开更多
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 ...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.展开更多
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...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.展开更多
Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leadi...Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Remote sensing has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil salinity can be identified from remote sensing data obtained by different sensors by way of direct indicators that refer to salt features that are visible at the soil surface as well as indirect indicators such as the presence of halophytic plant and assessing the performance level of salt-tolerant crops. The purposes of this paper are to 1) discuss some soil salinity indicators;2) review the satellite sensors and methods used for remote monitoring, detecting and mapping of soil salinity, particularly in arid and semi-arid regions;3) review various spectral vegetation and salinity indices that have been developed and proposed for soil salinity detection and mapping, with an emphasis on soil salinity mapping and assessment in arid and semi-arid regions;and 4) highlight the most important issues limiting the use of remote sensing for soil salinity mapping, particularly in arid and semi-arid regions.展开更多
The North China Plain (NCP) lying along the eastern coastal area withgeogriaphical coordinates 100°to 120°and 30° to 40°W, is one of the mostimportan agncultural ngons in China. A problem in soil s...The North China Plain (NCP) lying along the eastern coastal area withgeogriaphical coordinates 100°to 120°and 30° to 40°W, is one of the mostimportan agncultural ngons in China. A problem in soil salmization has beenfound in vast areas along the lower reaches of the Yellow hiver and north of it. After30 years of work on saline soil amelioration, 2.0 million ha has been improved,accounting for over 60 percen of the total ongnal saline soil area. Ths achievetnenthas ban obtained in close relation to water conservancy work. The author analyzessalthezation amelioration by using measures concerning subsuffoce water regulation.Ih addition to water conservancy measures, thes paper also descnbes acomprehensive way to ameliorate salthezation in northem NCP. Finally, the authorstresses the necessity of combining all measures together into a whole system forsolving salinization problems in northem NCP.展开更多
Over the past five decades, increased pressure caused by the rapidly growing population has resulted in a reclamation of agricultural and urban buffer zones along China's coastline. However, information about the ...Over the past five decades, increased pressure caused by the rapidly growing population has resulted in a reclamation of agricultural and urban buffer zones along China's coastline. However, information about the spatio–temporal variation of soil salinity in these reclaimed regions is limited. As such, obtaining this information is crucial for mapping the variation in saline areas and to identify suitable salinity management strategies. In this study, we employed EM38 data to conduct digital soil mapping of spatio–temporal variation and map these variations of different site-specific zones. The results indicated that the distribution of soil salinity was heterogeneous in the middle of, and that the leaching of salts was significant at the edges of, the study field. Afterwards, fuzzy-k means algorithm was used to divide the site-specific management zones within the time series apparent soil electrical conductivity(ECa) data and the spatial correlations of variation. We concluded that two management zones are optimal to guide precision management. Zone A had an average salinity level of about 165 mS m–1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil. In Zone B, there was a low salinity level with a mean of 89 mS m–1 for ECa, which allows for rice, wheat, and a wide range of vegetables to be grown normally. In such situations, measures such as an optimized combination of irrigation and drainage, as well as soil amendment can be taken to adjust and control the salt content. Particularly, flattening the land with a large-scale machine was used to improve the ability of micro-topography to influence salt migration; rice and other dry, land crops were planted in rotation in combination with utilizing salt-leaching multiple times to speed up desalinization.展开更多
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 e...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.展开更多
Soil salinity limits plant growth, reduces crop productivity and degrades soil. Multispectral data from Landsat TM are used to study saline soils in southern Tunisia. This study will explore the potential multivariate...Soil salinity limits plant growth, reduces crop productivity and degrades soil. Multispectral data from Landsat TM are used to study saline soils in southern Tunisia. This study will explore the potential multivariate statistical analysis, such as principal component analysis (PCA) and cluster analysis to identify the most correlated spectral indices and rapidly predict salt affected soils. Sixty six soil samples were collected for ground truth data in the investigated region. A high correlation was found between electrical conductivity and the spectral indices from near infrared and short-wave infrared spectrum. Different spectral indices were used from spectral bands of Landsat data. Statistical correlation between ground measurements of Electrical Conductivity (EC), spectral indices and Landsat original bands showed that the near and short-wave infrared bands (band 4, band 5 and 7) and the salinity indices (SI 5 and SI 9) have the highest correlation with EC. The use of CA revealed a strong correlation between electrical conductivity EC and spectral indices such abs4, abs5, abs7 and si5. The principal components analysis is conducted by incorporating the reflectance bands and spectral salinity indices from the remote sensing data. The first principal component has large positive associations with bands from the visible domain and salinity indices derived from these bands, while second principal component is strongly correlated with spectral indices from NIR and SWIR. Overall, it was found that the electrical conductivity EC is highly correlated (R2 = -0.72) to the second principal component (PC2), but no correlation is observed between EC and the first principal component (PC1). This suggests that the second component can be used as an explanatory variable for predicting EC. Based on these results and combining the spectral indices (PC2 and abs B4) into a regression analysis, model yielded a relatively high coefficient of determination R2 = 0.62 and a low RMSE = 1.86 dS/m.展开更多
Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to...Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.展开更多
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 spa...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 SO_4^(2-) and Cl^-, while cations were mainly Na^+ and Ca^(2+);(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.展开更多
To test the variation and transport of soil salinity in saline- alkali land under water storage and drainage treatments,an experimental model was established in Fuping,Shaanxi Province,2009. The variation of soil sali...To test the variation and transport of soil salinity in saline- alkali land under water storage and drainage treatments,an experimental model was established in Fuping,Shaanxi Province,2009. The variation of soil salinity during 0- 160 cm soil depth under the two treatments was determined and analyzed. Results showed that the average soil water content under water storage treatment was 4. 47% higher than that under drainage treatment,which means that the water storage treatment could help to improve soil moisture to satisfy the crop's growth needs. The profile distribution of soil soluble solids( TDS),anion( Cl-,HCO3-,SO2-4) and cation( Ca2 +,Na+,K+) content and the variation of soil p H were also measured and analyzed. PCA( Principal Component Analysis) was used to explore the relationship between the soil salinity and its ions,which showed that the water storage treatment could significantly decrease the surface salinity of soil and accelerate the desalination of topsoils,and finally,the soil quality was improved significantly,demonstrating that the water storage treatment has a remarkable effect on soil salinity management.展开更多
In arid and semi-arid regions, salinity is a serious and chronic problem for agriculture. The aim of this study is to evaluate the hydromorphical and salinity risks, and to evaluate the relationship and the possible i...In arid and semi-arid regions, salinity is a serious and chronic problem for agriculture. The aim of this study is to evaluate the hydromorphical and salinity risks, and to evaluate the relationship and the possible interfering between the water table and the soil on the oasis of Gabes. The topic is very important, especially for nations around the oceans in arid and semi-arid regions. The effect of the gypsum alkalinity in the soil salinity has investigated. The chemical characteristic of used water irrigation (salinity saturation) and their impact factor in the productivity area. Moreover, in this study the program of examination need to put fifteen piesometres by CRAD (Regional Commissariat of Agriculture Development) in the city of Gabes to controlling the variation of water levels in the superficial water table and their change chemical quality. The experimental measure of this program needs a yearly observation and investigation during April and May to evaluate the hydromorphical and salinity risks on the oasis of Gabes. The relationship and the possible interfering between the water table and the soil has evaluate in such condition.展开更多
In order to get RS method to extract soil salinity of the Yellow River Delta, we set Kenli County as typical Yellow River Delta to be research area and get data of soil salinity through field investigation. By using R...In order to get RS method to extract soil salinity of the Yellow River Delta, we set Kenli County as typical Yellow River Delta to be research area and get data of soil salinity through field investigation. By using RS image of Landsat-8 of March 14, 2014 and analyzing information features of each band and surface spectral features of research areas, we select out sensitive bands and build Soil Salinity Information Extraction (SSIE) model and vegetation index NDVI model for comparison. And then, we accordingly classify grades of soil salinity and get soil salinity information by decision tree approach based on expert knowledge. The results show that overall accuracy of SSIE model is 93.04% and coefficient of Kappa is 0.7869, while overall accuracy of NDVI model is 83.67% and coefficient of Kappa is 0.7017 respectively. By comparing with measured proportions of each class, we see that results from SSIE model is more accurate, which indicates significant advantage for soil salinity information extraction. This research provides scientific basis to get and monitoring soil salinity of the Yellow River Delta region quickly and accurately.展开更多
文摘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 CO<sub>2</sub> 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 CO<sub>2 </sub>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.
文摘The estuary tides affect groundwater dynamics;these areas are susceptible to waterlogging and salinity issues.A study was conducted on two fields with a total area of 60 hectares under a center pivot irrigation system that works with solar energy and belong to a commercial farm located in Northern Sudan.To monitor soil salinity and calcium carbonate in the area and stop future degradation of soil resources,easy,non-intrusive,and practical procedures are required.The objective of this study was to use remote sensing-determined Sentinel-2 satellite imagery using various soil indices to develop prediction models for the estimation of soil electrical conductivity(EC)and soil calcium carbonate(CaCO_(3)).Geo-referenced soil samples were collected from 72 locations and analyzed in the laboratory for soil EC and CaCO_(3).The electrical conductivity of the soil saturation paste extract was represented by average values in soil dataset samples from two fields collected from the topsoil layer(0 to 15 cm)characteristic of the local salinity gradient.The various soil indices,used in this study,were calculated from the Sentinel-2 satellite imagery.The prediction was determined using the root mean square error(RMSE)and cross validation was done using coefficient of determination.The results of regression analysis showed linear relationships with significant correlation between the EC analyzed in laboratory and the salinity index-2“SI2”(Model-1:R^(2)=0.59,p=0.00019 and root mean square error(RMSE=1.32%)and the bare soil index“BSI”(Model-2:R^(2)=0.63,p=0.00012 and RMSE=6.42%).Model-1 demonstrated the best model for predicting soil EC,and validation R^(2)and RMSE values of 0.48%and 1.32%,respectively.The regression analysis results for soil CaCO_(3)determination showed linear relationships with data obtained in laboratory and the bare soil index“BSI”(Model-3:R^(2)=0.45,p=0.00021 and RMSE=1.29%)and the bare soil index“BSI”&Normalized difference salinity index“NDSI”(Model-4:R^(2)=0.53,p=0.00015 and RMSE=1.55%).The validation confirmed the Model-3 results for prediction of soil CaCO_(3)with R^(2)and RMSE values of 0.478%and 1.29%,respectively.Future soil monitoring programs might consider the use of remote sensing data for assessing soil salinity and CaCO_(3)using soil indices results generated from satellite image(i.e.,Sentinel-2).
文摘In response to the global food crisis and the imperative to address soil degradation, the international agricultural policy is actively working to alleviate the adverse impacts of soil salinity. As part of this initiative, a field trial spanning two consecutive seasons (2019/20-2020/21) was conducted under saline conditions. The primary objective was to evaluate the influence of various compost sources, including vermicompost at a rate of 0.5 ton·fed<sup>-1</sup> and plant residues compost at a rate of 5.0 ton·fed<sup>-1</sup>, as main plots. Subplots were established by applying agricultural gypsum, both in the presence and absence of gypsum requirements. Additionally, sub-subplots were created by externally applying cobalt at a rate of 10.0 mg·L<sup>-1</sup>, with one sub-subplot receiving foliar cobalt application and the other not. The trial sought to assess the growth performance, chemical composition, enzymatic antioxidants, yield, and quality of cabbage plants (Brassica oleracea var. capitata L.) cultivated in saline soil. According to the findings, cabbage plants exhibited the most favorable response in terms of plant height, chlorophyll content, carotene levels, leaf area, nitrogen (N), phosphorus (P), potassium (K), head yield, vitamin C, and total dissolved solids (TDS) when treated with vermicompost, followed by plant compost. Conversely, plants grown without compost exhibited the least improvement in performance. Cabbage treated with agricultural gypsum requirements showed better performance than those without gypsum amendment. Moreover, plants subjected to cobalt spray demonstrated the highest growth, yield, and quality parameters compared to those without cobalt foliar application. In contrast, the control group (plants without the studied treatments) displayed the highest levels of enzymatic antioxidants, specifically catalase and peroxidase. This indicates that soil salinity stress led to an increase in catalase and peroxidase production in cabbage plants as a defense against the harmful impact of reactive oxygen species (ROS) resulting from soil salinity stress. The applied treatments (compost, gypsum, and cobalt) led to a reduction in the cabbage plant’s inherent production of catalase and peroxidase. Generally, the combined treatment of vermicompost × gypsum requirements × cobalt proved effective in mitigating the detrimental effects of soil salinity on cabbage plants. These findings hold significance for farmers and policymakers aiming to enhance agricultural productivity in regions affected by soil salinity. Additionally, further research can explore the long-term effects of these treatments on soil health and crop sustainability.
文摘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.
文摘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.
文摘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.
文摘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.
基金Under the auspices of the Strategic Priority Research Program of the Chinese Academy of Sciences(No.XDA28110301,XDA2306040303)National Natural Science Foundation of China(No.41807001,41977424)Natural Science Foundation of Jilin Province(No.20200201026JC)。
文摘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.
基金Sponsored by Science and Technology Project of Key Technology for Control of Major Production Accidents in 2015(shandong-0017-2015AQ)National Natural Science Foundation of Shandong Province,China(ZR2015PC022)
文摘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.
文摘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.
文摘Soil salinity is a serious environmental problem especially in arid and semiarid areas. It either occurs naturally or is human-induced. High levels of soil salinity negatively affect crop growth and productivity leading land degradation ultimately. Thus, it is important to monitor and map soil salinity at an early stage to enact effective soil reclamation program that helps lessen or prevent future increase in soil salinity. Remote sensing has outperformed the traditional method for assessing soil salinity offering more informative and professional rapid assessment techniques for monitoring and mapping soil salinity. Soil salinity can be identified from remote sensing data obtained by different sensors by way of direct indicators that refer to salt features that are visible at the soil surface as well as indirect indicators such as the presence of halophytic plant and assessing the performance level of salt-tolerant crops. The purposes of this paper are to 1) discuss some soil salinity indicators;2) review the satellite sensors and methods used for remote monitoring, detecting and mapping of soil salinity, particularly in arid and semi-arid regions;3) review various spectral vegetation and salinity indices that have been developed and proposed for soil salinity detection and mapping, with an emphasis on soil salinity mapping and assessment in arid and semi-arid regions;and 4) highlight the most important issues limiting the use of remote sensing for soil salinity mapping, particularly in arid and semi-arid regions.
文摘The North China Plain (NCP) lying along the eastern coastal area withgeogriaphical coordinates 100°to 120°and 30° to 40°W, is one of the mostimportan agncultural ngons in China. A problem in soil salmization has beenfound in vast areas along the lower reaches of the Yellow hiver and north of it. After30 years of work on saline soil amelioration, 2.0 million ha has been improved,accounting for over 60 percen of the total ongnal saline soil area. Ths achievetnenthas ban obtained in close relation to water conservancy work. The author analyzessalthezation amelioration by using measures concerning subsuffoce water regulation.Ih addition to water conservancy measures, thes paper also descnbes acomprehensive way to ameliorate salthezation in northem NCP. Finally, the authorstresses the necessity of combining all measures together into a whole system forsolving salinization problems in northem NCP.
基金funded by the National Natural Science Foundation of China (41601213)the National Key Research and Development Program of China (2017YFD0700501)the Major Science and Technology Projects of Henan, China (171100110600)
文摘Over the past five decades, increased pressure caused by the rapidly growing population has resulted in a reclamation of agricultural and urban buffer zones along China's coastline. However, information about the spatio–temporal variation of soil salinity in these reclaimed regions is limited. As such, obtaining this information is crucial for mapping the variation in saline areas and to identify suitable salinity management strategies. In this study, we employed EM38 data to conduct digital soil mapping of spatio–temporal variation and map these variations of different site-specific zones. The results indicated that the distribution of soil salinity was heterogeneous in the middle of, and that the leaching of salts was significant at the edges of, the study field. Afterwards, fuzzy-k means algorithm was used to divide the site-specific management zones within the time series apparent soil electrical conductivity(ECa) data and the spatial correlations of variation. We concluded that two management zones are optimal to guide precision management. Zone A had an average salinity level of about 165 mS m–1, in which salt-tolerant crops, such as cotton and barley can grow normally, while crops such as soybean and cowpeas may be planted using leaching and increasing the mulching film methods to reduce the accumulation of salt in surface soil. In Zone B, there was a low salinity level with a mean of 89 mS m–1 for ECa, which allows for rice, wheat, and a wide range of vegetables to be grown normally. In such situations, measures such as an optimized combination of irrigation and drainage, as well as soil amendment can be taken to adjust and control the salt content. Particularly, flattening the land with a large-scale machine was used to improve the ability of micro-topography to influence salt migration; rice and other dry, land crops were planted in rotation in combination with utilizing salt-leaching multiple times to speed up desalinization.
基金supported by the Fundamental Research Funds for the Central Universities(Grant No.2016B14614)the Program of China Scholarship Council(Grant No.201906715015)+1 种基金the National Key Research and Development Program of China(Grant No.2017YFC040320502)a project funded by the Priority Academic Program Development(PAPD)of Jiangsu Higher Education Institutions.
文摘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.
文摘Soil salinity limits plant growth, reduces crop productivity and degrades soil. Multispectral data from Landsat TM are used to study saline soils in southern Tunisia. This study will explore the potential multivariate statistical analysis, such as principal component analysis (PCA) and cluster analysis to identify the most correlated spectral indices and rapidly predict salt affected soils. Sixty six soil samples were collected for ground truth data in the investigated region. A high correlation was found between electrical conductivity and the spectral indices from near infrared and short-wave infrared spectrum. Different spectral indices were used from spectral bands of Landsat data. Statistical correlation between ground measurements of Electrical Conductivity (EC), spectral indices and Landsat original bands showed that the near and short-wave infrared bands (band 4, band 5 and 7) and the salinity indices (SI 5 and SI 9) have the highest correlation with EC. The use of CA revealed a strong correlation between electrical conductivity EC and spectral indices such abs4, abs5, abs7 and si5. The principal components analysis is conducted by incorporating the reflectance bands and spectral salinity indices from the remote sensing data. The first principal component has large positive associations with bands from the visible domain and salinity indices derived from these bands, while second principal component is strongly correlated with spectral indices from NIR and SWIR. Overall, it was found that the electrical conductivity EC is highly correlated (R2 = -0.72) to the second principal component (PC2), but no correlation is observed between EC and the first principal component (PC1). This suggests that the second component can be used as an explanatory variable for predicting EC. Based on these results and combining the spectral indices (PC2 and abs B4) into a regression analysis, model yielded a relatively high coefficient of determination R2 = 0.62 and a low RMSE = 1.86 dS/m.
基金Under the auspices of National Natural Science Foundation of China(No.41571217)National Program on Key Basic Research Project(No.2016YFD0300801)
文摘Timely monitoring and early warning of soil salinity are crucial for saline soil management. Environmental variables are commonly used to build soil salinity prediction model. However, few researches have been done to summarize the environmental sensitive variables for soil electrical conductivity(EC) estimation systematically. Additionally, the performance of Multiple Linear Regression(MLR), Geographically Weighted Regression(GWR), and Random Forest regression(RFR) model, the representative of current main methods for soil EC prediction, has not been explored. Taking the north of Yinchuan plain irrigation oasis as the study area, the feasibility and potential of 64 environmental variables, extracted from the Landsat 8 remote sensed images in dry season and wet season, the digital elevation model, and other data, were assessed through the correlation analysis and the performance of MLR, GWR, and RFR model on soil salinity estimation was compared. The results showed that: 1) 10 of 15 imagery texture and spectral band reflectivity environmental variables extracted from Landsat 8 image in dry season were significantly correlated with soil EC, while only 3 of these indices extracted from Landsat 8 image in wet season have significant correlation with soil EC. Channel network base level, one of the terrain attributes, had the largest absolute correlation coefficient of 0.47 and all spatial location factors had significant correlation with soil EC. 2) Prediction accuracy of RFR model was slightly higher than that of the GWR model, while MLR model produced the largest error. 3) In general, the soil salinization level in the study area gradually increased from south to north. In conclusion, the remote sensed imagery scanned in dry season was more suitable for soil EC estimation, and topographic factors and spatial location also play a key role. This study can contribute to the research on model construction and variables selection for soil salinity estimation in arid and semiarid regions.
基金funded by the National Natural Science Foundation of China (Nos. 41201032, 41561073, and U1138302)
文摘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 SO_4^(2-) and Cl^-, while cations were mainly Na^+ and Ca^(2+);(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.
基金Supported by National Science and Technology Support Program(2014BAL01B03)
文摘To test the variation and transport of soil salinity in saline- alkali land under water storage and drainage treatments,an experimental model was established in Fuping,Shaanxi Province,2009. The variation of soil salinity during 0- 160 cm soil depth under the two treatments was determined and analyzed. Results showed that the average soil water content under water storage treatment was 4. 47% higher than that under drainage treatment,which means that the water storage treatment could help to improve soil moisture to satisfy the crop's growth needs. The profile distribution of soil soluble solids( TDS),anion( Cl-,HCO3-,SO2-4) and cation( Ca2 +,Na+,K+) content and the variation of soil p H were also measured and analyzed. PCA( Principal Component Analysis) was used to explore the relationship between the soil salinity and its ions,which showed that the water storage treatment could significantly decrease the surface salinity of soil and accelerate the desalination of topsoils,and finally,the soil quality was improved significantly,demonstrating that the water storage treatment has a remarkable effect on soil salinity management.
文摘In arid and semi-arid regions, salinity is a serious and chronic problem for agriculture. The aim of this study is to evaluate the hydromorphical and salinity risks, and to evaluate the relationship and the possible interfering between the water table and the soil on the oasis of Gabes. The topic is very important, especially for nations around the oceans in arid and semi-arid regions. The effect of the gypsum alkalinity in the soil salinity has investigated. The chemical characteristic of used water irrigation (salinity saturation) and their impact factor in the productivity area. Moreover, in this study the program of examination need to put fifteen piesometres by CRAD (Regional Commissariat of Agriculture Development) in the city of Gabes to controlling the variation of water levels in the superficial water table and their change chemical quality. The experimental measure of this program needs a yearly observation and investigation during April and May to evaluate the hydromorphical and salinity risks on the oasis of Gabes. The relationship and the possible interfering between the water table and the soil has evaluate in such condition.
文摘In order to get RS method to extract soil salinity of the Yellow River Delta, we set Kenli County as typical Yellow River Delta to be research area and get data of soil salinity through field investigation. By using RS image of Landsat-8 of March 14, 2014 and analyzing information features of each band and surface spectral features of research areas, we select out sensitive bands and build Soil Salinity Information Extraction (SSIE) model and vegetation index NDVI model for comparison. And then, we accordingly classify grades of soil salinity and get soil salinity information by decision tree approach based on expert knowledge. The results show that overall accuracy of SSIE model is 93.04% and coefficient of Kappa is 0.7869, while overall accuracy of NDVI model is 83.67% and coefficient of Kappa is 0.7017 respectively. By comparing with measured proportions of each class, we see that results from SSIE model is more accurate, which indicates significant advantage for soil salinity information extraction. This research provides scientific basis to get and monitoring soil salinity of the Yellow River Delta region quickly and accurately.
