Soil Salt Content Research Articles

Spatial Variations and Distribution Patterns of Soil Salinity at the Canal Scale in the Hetao Irrigation District

Soil salinization is a major factor impacting global crop yields. To explore the spatial distribution and influencing factors of soil water and salt in typical canals of the Hetao irrigation district, regional soil information was monitored at fixed locations. In this study, classical statistics, geostatistics, and spatial autocorrelation methods were used to conduct quantitative analyses of soil salt content, water content, soil particle size distribution, and groundwater depth. The variation coefficient of the soil salt content in the 20–40 and 40–60 cm soil layers was between 10% and 100%, which corresponds to a medium degree of variation; the other soil layers had strong degrees of variation. The soil moisture content in each layer varied moderately. The gold coefficients of soil salt content and water content were less than 0.25, and the Z value was greater than 0, showing a strong spatial correlation and certain spatial agglomeration characteristics, which were mainly affected by structural factors in the study area. The distribution patterns of soil water and salt were affected by soil particle size. Sand content decreased with increasing depth, soil salt was negatively correlated with sand content, and soil water was positively correlated with sand content. Soil salinity was significantly affected by groundwater depth and increased with decreasing groundwater depth, following an exponential relationship. When the groundwater depth exceeded 1.7 m, the soil salt content exhibited small changes with groundwater depth. The results of this study could play a guiding role in terms of understanding the degree of soil salinization surrounding canals in the Hetao irrigation area and adjusting land management strategies over time.

Agrivoltaic approach in improving soil resistivity in large scale solar farms for energy sustainability

Recently, approaches have been established to improve the grounding system performance, especially with the increasing numbers of large-scale solar (LSS) PV farms. Soil resistivity is one of the contributing factors to the inefficiency of power generation as it induces high impedance on electricity flow from the source to highly sensitive PV equipment and devices such as inverters. Some critical issues on nutrient leaching derived from ammonium sulphate fertilizer direct to ground soil are the focal point of this work with the fact that soil resistivity value is inversely proportional to increasing soil salt content. Therefore, a low grounding system could be obtained with a high Electrical Conductivity (EC) and high soil moisture content. In this work, a conceptual setup for an agrivoltaic condition with 500 units of herbal crops has been cultivated directly underneath 1 PV string in Puchong Solar Farm, Selangor, Malaysia. The amount of salt or nutrient under this condition was measured leaching approximately 40 mL per polybag as means of ground treatment to improve soil resistivity value, thus indirectly reducing the risk of electrical damage. The agrivoltaic approach has shown that it can improve the performance of a grounding system in an LSS PV farm with a significant reduction of 4.45 Ω earth resistance on average.

Spatiotemporal Variation and Future Predictions of Soil Salinization in the Werigan–Kuqa River Delta Oasis of China

Soil salinization is a serious global issue; by 2050, without intervention, 50% of the cultivated land area will be affected by salinization. Therefore, estimating and predicting future soil salinity is crucial for preventing soil salinization and investigating potential arable land resources. In this study, several machine learning methods (random forest (RF), Light Gradient Boosting Machine (LightGBM), Gradient Boosting Decision Tree (GBDT), and eXtreme Gradient Boosting (XGBoost)) were used to estimate the soil salinity in the Werigan–Kuqa River Delta Oasis region of China from 2001 to 2021. The cellular automata (CA)–Markov model was used to predict soil salinity types from 2020 to 2050. The LightGBM method exhibited the highest accuracy, and the overall prediction accuracy of the methods had the following order: LightGBM > RF > GBRT > XGBoost. Moderately saline, severely saline, and saline soils were dominant in the east and south of the research area, while non-saline and mildly saline soils were widely distributed in the inner oasis area. A marked decreasing trend in the soil salt content was observed from 2001 to 2021, with a decreasing rate of 4.28 g/kg·10 a−1. The primary change included the conversion of mildly and severely saline soil types to non-saline soil. The generalized difference vegetation index (51%), Bio (30%), and temperature vegetation drought index (27%) had the greatest influence, followed by variables associated with soil attributes (soil organic carbon and soil organic carbon stock) and terrain (topographic wetness index, slope, aspect, curvature, and topographic relief index). Overall, the CA–Markov simulation resulted exhibited suitable accuracy (kappa = 0.6736). Furthermore, areas with non-saline and mildly saline soils will increase while areas with other salinity levels will continue to decrease from 2020 to 2050. From 2046 to 2050, numerous areas with saline soil will be converted to non-saline soil. These results can provide support for salinization control, agricultural production, and soil investigations in the future. The gradual decline in soil salinization in the research area in the past 20 years may have resulted from large-scale land reclamation, which has turned saline alkali land into arable land and is also related to effective measures taken by the local government to control salinization.

Study On the Application of Nitro-Compound Fertilizer to Improve Saline-Alkali Soil

The deterioration of soil quality in saline-alkali land has always been a major problem restricting the development of agriculture in China. Therefore, this study studied the application effect of nitro-compound fertilizer through experiments, aiming to explore the application prospect and popularization value of nitro-compound fertilizer in saline-alkali land agriculture. The experimental results showed that nitro-compound fertilizer could significantly improve the soil quality and increase the yield and growth of crops in saline-alkali soil. The addition amount of 2.5-10 kg/ mu is more suitable, and the addition of 10 kg/ mu of nitro-compound fertilizer can increase the yield of corn by 217%. In addition, the addition of nitro-compound fertilizer can not only significantly reduce the soil salt content, the reduction can reach 37.5%, but also significantly improve the soil alkalinity. pH value decreased from the original 9.4 to 7.12, a decrease of 2.28. This showed that the application of nitro-compound fertilizer had a remarkable improvement effect in regulating soil alkalinity. Therefore, the application of nitro-compound fertilizer has wide application prospect and popularization value in saline-alkali land agriculture.

Features of Soil Bacterial Communities of Varying Degree of Salinity on the Example of the Shaulder Irrigation Massif of the Turkestan Region of the Republic of Kazakhstan

A comparative assessment of bacterial communities of meadow-serozem soils of different degrees of salinity was carried out. Significant differences in the structure of microbiomes of arable horizons of weakly saline and highly saline meadow-serozem soil were revealed. A significant reduction in the diversity of the microbiome at the phylum level with an increase in the level of soil salinity was established (on the example of meadow-serozem soils of the Shaulder irrigation massif). The structure of bacterial communities of the meadow-serozem highly saline soil is represented by four bacterial phyla: (Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria), while 13 bacterial phyla were identified in weakly salinized soil (Proteobacteria, Actinobacteria, Bacteroidetes, Verrucomicrobia, Acidobacteria, Chloroflexi, Firmicutes, Gemmatimonadetes, Planctomycetes, Saccharibacteria, Cyanobacteria, Chlorobi, Nitrospirae). According to the Shannon index, the species diversity of the microbiome of the meadow-serozem soils of the Shaulder irrigation massif is about 20% higher on weakly saline soils compared to highly saline ones. The Chao1 index and the number of taxonomic units (OTUs) also indicate a roughly halving of alpha diversity in the highly saline soil microbiome. The ecological significance of the problem of secondary soil salinization was confirmed. With an increase of salt content in soils, the species diversity of the bacterial community decreases, which can be considered as one of the indicators of soil degradation.

Effective strategies for reclamation of saline-alkali soil and response mechanisms of the soil-plant system

The combination of amendments has emerged as a potential strategy to efficiently alleviate salt stress in saline-alkali soil. However, knowledge regarding how to optimize the proportion of different amendment materials, comprehensively assess the contribution of each component, and clarify the response mechanisms of the amendment-saline-alkali soil-plant system is incomplete. Based on this, we conducted a pot experiment to evaluate the improvement effect of the combined application of different amendment materials at varying levels and the contribution of the amendment components to alleviating salt stress. Overall, T6 exhibited the most significant improvement effect on the physicochemical and biological properties of the saline-alkali soil and promoted the growth of oilseed rape, with the levels of 2.0 % phosphogypsum, 2.0 % humic acid, 0.25 % bentonite, and 0.03 % sodium carboxymethyl cellulose. Compared with the control group, the EC decreased by 1.51 % to 33.49 %, the soil salt content dropped by 11.40 % to 35.46 %, and the soil soluble Na + concentration significantly declined by 39.47 % to 63.20 %. Additionally, the soil nutrient content and soil microbial community structure were enhanced in treatment groups. Meanwhile, amendments alleviated salt stress in the oilseed rape plant by activating anti-oxidative enzymes and osmoregulatory substances such as soluble sugar and proline, thus improving their ability to remove reactive oxygen species (ROS). The anti-oxidative enzymes such as superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT) were significantly increased, with an increase of 10.68 % (SOD, T2) ∼207.31 % (CAT, T6) compared to the control group. The structural equation modeling (SEM) analysis and simulation experiments indicated that the amendment components synergically promoted the amelioration effect on salt stress, and effectively improved soil properties, which affected the response of oilseed rape to soil environment. This research paper provides the relevant reference for the combined application of different amendment materials for soil reclamation.

Optimizing biochar application rates for improved soil chemical environments in cotton and sugarbeet fields under trickle irrigation with plastic mulch

Biochar can potentially change the soil physico-chemical environment significantly, but its impact on the soil chemical environment is poorly understood. To investigate this, a three-year field experiment with drip irrigation under plastic film mulch was conducted from 2018 to 2020 in a saline-alkali cotton and sugarbeet field in Xinjiang, China. The experiment examined the influences of different biochar application rates (BAR) on the distribution and variations of soil Na+ and K+ contents, soil nutrient contents (NO3–-N, NH4+-N, soil organic carbon, available phosphorus, and available potassium), soil salt content and accumulation. Four BAR treatments of 0, 10, 50, and 100 t ha–1, namely CK, B10, B50, and B100 were designed in 2018, with adjusted in 2019 and 2020 based on the former 2 year’s results, namely CK, B10, B25 (25 t ha–1), B50, and B100 in 2019, and CK, B10, B25, and B30 (30 t ha–1) in 2020. The results indicated that increasing BAR significantly increased Na+, K+, and soil nutrient contents in cotton and sugarbeet fields. Soil salinity were the highest in inter-rows, followed by narrow and wide rows, and salt accumulated at 0–60 cm depth the most. Weighted-average planar soil salt storage positively correlated with BAR, with lower soil salt contents for sugarbeet than cotton at the same depth. Based on the effects of different BAR on soil ion concents, soil nutrients, and soil salinity, we recommended 10 t ha−1 as an optimal BAR for improving the chemical environment of saline-alkali soil, and sugarbeet as an effective crop for reducing soil salinity. These findings provided valuable technique parameters for biochar application in saline-alkali land.

Estimating and Mapping Soil Salinity in Multiple Vegetation Cover Periods by Using Unmanned Aerial Vehicle Remote Sensing

Soil salinization is a severe soil degradation issue in arid and semiarid regions. The distribution of soil salinization can prove useful in mitigating soil degradation. Remote sensing monitoring technology is available for obtaining the distribution of soil salinization rapidly and nondestructively. In this study, experimental data were collected from seven study areas of the Hetao Irrigation District from July to August in 2021 and 2022. The soil salt content (SSC) was considered at various soil depths, and the crop type and time series were considered as environmental factors. We analyzed the effects of various environmental factors on the sensitivity response of unmanned aerial vehicle (UAV)-derived spectral index variables to the SSC and assessed the accuracy of SSC estimations. The five indices with the highest correlation with the SSC under various environmental factors were the input parameters used in modeling based on three machine learning algorithms. The best model was subsequently used to derive prediction distribution maps of the SSC. The results revealed that the crop type and time series did not affect the relationship strength between the SSC and spectral indices, and that the classification of the crop type and time series can considerably enhance the accuracy of SSC estimation. The mask treatment of the soil pixels can improve the correlation between some spectral indices and the SSC. The accuracies of the ANN and RFR models were higher than SVR accuracy (optimal R2 = 0.52–0.79), and the generalization ability of ANN was superior to that of RFR. In this study, considering environmental factors, a UAV remote sensing estimation and mapping method was proposed. The results of this study provide a reference for the high-precision prediction of soil salinization during the vegetation cover period.

Decoupling of nutrient stoichiometry in Suaeda glauca (Bunge) senesced leaves under salt treatment.

The stoichiometry of senesced leaves is pivotal in nutrient cycling and can be significantly influenced by soil salinization, a rising global issue threatening the functionality of ecosystems. However, the impacts of soil salinization on senesced leaf stoichiometry are not fully understood. In this study, we conducted a pot experiment with varying soil salt concentrations to examine their influence on the concentrations and stoichiometric ratios of nitrogen (N), phosphorus (P), sodium (Na), potassium (K), calcium (Ca), magnesium (Mg), and zinc (Zn) in the senesced leaves of Suaeda glauca (Bunge). Compared to the control group, salt treatments significantly enhanced Na concentration while diminishing the concentrations of K, Ca, Mg, Zn, N, and P. Interestingly, as salinity levels escalated, N concentration maintained stability, whereas P concentration exhibited an increasing trend. Moreover, K, Ca, and Mg significantly declined as salt levels rose. Salt treatments brought about significant changes in stoichiometric ratios, with the N:P, K:Na, N:Na, N:Mg, and Ca : Mg ratios dropping and the N:Ca and N:K ratios rising, illustrating the varying nutrient coupling cycles under different salt conditions. These findings shed light on the plasticity of stoichiometric traits in S. glauca senesced leaves in response to soil salinization shifts, which could potentially offer insights into nutrient cycling reactions to soil salinization.

Diversity of soil seed bank and influencing factors in the nascent wetland of the Yellow River Delta.

Soil seed bank is the growth and reproduction source of vegetation community, playing an important role in vegetation establishment, succession and renewal, biodiversity maintenance. This study has selected the nascent wetland in the Yellow River Delta (YRD) formed in 1996 as study area and investigated the diversity and key influencing factors of soil seed bank diversity. The study results show that: (1) The soil seed bank in the study area has a simple structure, containing relatively few species. A total of five plant species, which belong to four families and five genera, were found in this bank, with Phragmites australis and Suaeda salsa being the dominant plants. (2) All species are herbs without woody species. One herb is annual herb and the others are perennial herbs. (3) From the sea to the river, the changes rules of the overall density and diversity of the seed bank are not obvious. (4) The dispersal distance from salt and freshwater has a significant influence on the density of the soil seed bank but has no significant influence on the diversity. Meanwhile, the soil salt content has a significant negative influence on the diversity of seed banks. (5) Aboveground vegetation did not closely relationship with diversity of soil seed bank. All above results can provide basic data and scientific evidence for the conservation of vegetation communities in the nascent wetlands and vegetation restoration in the degraded wetlands in the YRD.

Study on Water and Salt Transport under Different Subsurface Pipe Arrangement Conditions in Severe Saline–Alkali Land in Hetao Irrigation District with DRAINMOD Model

As an effective method to improve saline–alkali land, the drainage from subsurface pipes has been extensively studied in typical arid and semi-arid agricultural areas (Hetao Irrigation District). However, there are few studies on the improvement of subsurface pipe layout and the long-term soil salinization control in the process of leaching and soil amendment with subsurface pipes in this area. This study investigated the water and salt migration in the process of amending the heavy saline soil. Field experiments growing sunflowers and numerical model calculation were combined in this research. It was found in the field experiment that the salt concentration in the surface pipe drainage was positively correlated with the salt content in the soil and the depth of the pipe, while it was negatively correlated with the amount of irrigation water and the spacing of crops. Thus, the soil desalting rate (N) and salt control rate (SCR) were positively correlated with the depth of the pipe, and they were negatively correlated with the spacing. The leaching effect of irrigation would decrease when the soil salt content decreased. On the basis of field experiments, the DRAINMOD model and drainmod equation were used to calculate the water and salt migration in 38 different field plots during 2019 and 2020. When N was the same, the soil salinity in several plots with large burial depth could be controlled below the salt tolerance threshold of sunflowers during the growth period in the second year. The quantitative relationship between N and SCR, soil salt content before leaching, water amount of leaching, pipe spacing and buried depth was already established. These results can help develop strategies for desalination and salt control in the soil in the arid and semi-arid areas with the optimal layout of subsurface pipes.

Analysis of Water and Salt Spatio-Temporal Distribution along Irrigation Canals in Ningxia Yellow River Irrigation Area, China

The large amount of salinized soil in the Yellow River irrigation area is a threat to the sustainable development of agriculture, and in order to efficiently control the soil salinization trend, it is necessary to research water and salt variations and the distribution of soil in the area. In this study, soil salinization along two typical canals (West Main Canal and Tanglai Canal) in the Ningxia Yellow River irrigation area in China is investigated using data regarding water content, salt ions and pH from soil samples collected at 165 points along these canals. At each of these points, soil samples from various layers were collected for measurement from August 2019 to December 2020. Various methods, such as Pearson’s correlation analysis and Kriging interpolation, were employed to obtain the temporal and spatial distributions of water content, pH value and salt ions from the soil samples. It was found that the mean total salt value is 2.75 g/kg, which indicates that the soil in the study area is moderately salinized soil. The average value of soil pH is 8.5, indicating that the soil in this area is alkaline. Furthermore, it is evident that the coefficient of variation for certain soil ions, including HCO3−, Cl−, Ca2+, Na+ and K+, is greater than one, which indicates that their spatial distribution in the study area is severely uneven. Moreover, the soil salt content in the study area gradually increases from the southwest to the northeast, in the flow direction of the West Main Canal and the Tanglai Canal. The water content distribution along the two canals also exhibits notable non-uniformity, displaying a pattern higher in the north and east and less in the south and west. Moreover, the annual distribution of total salt content in the surface layer demonstrates an initial increase followed by a decrease, with the peak value typically occurring in August or September. The research results have an important significance on agriculture in the Ningxia Yellow River irrigation area.

Inversion Model of Salt Content in Alfalfa-Covered Soil Based on a Combination of UAV Spectral and Texture Information

This study aimed to investigate how the combination of texture information and spectral index affects the accuracy of the soil salinity inversion model. Taking the Bianwan Farm in Jiuquan City, Gansu Province, China as the research area, the multi-spectral data and soil salinity data at 0–15 cm, 15–30 cm and 30–50 cm depths in the sampling area under alfalfa coverage were collected, and spectral reflectance and texture features were obtained from a multispectral image. Moreover, the red-edge band was introduced to improve the spectral index, and gray correlation analysis was utilized to screen sensitive features. Five types of alfalfa-covered soil salinity machine learning inversion models based on random forest (RF) and extreme learning machine (ELM) algorithms were constructed, using the salinity index (SIs), vegetation index (VIs), salinity index + vegetation index (SIs + VIs), vegetation index + texture feature (VIs + TFs), and vegetation index + texture index (VIs + TIs). The determination coefficient R2, root-mean-square error (RMSE) and mean absolute error (MAE) were used to evaluate each model’s performance. The results show that the VIs model is more accurate than the SIs and SIs +VIs models. Combining texture information with VIs improves the inversion accuracy, and the VIs + TIs model has the best inversion effect. From the perspective of inversion depth, the inversion effect for 0–15 cm soil salinity was significantly better than that for other depths, and was the best inversion depth under alfalfa cover. The average R2 of the RF model was 10% higher than that of the ELM. The RF algorithm has high inversion accuracy and stability and performs better than ELM. These findings can serve as a theoretical basis for the efficient inversion of soil salinity and management of saline–alkali lands.

Investigation of Salt and Nitrogen Distribution under Belt Plastic Film Mulching in Surface- and Drip-Irrigated Maize Field in Hetao Irrigation District

Hetao Irrigation District (HID) is one of the main regions for maize and sunflower production in North China. However, water resource shortages and soil salinization greatly limit maize and sunflower production. The surface irrigation method is the main irrigation method in HID; however, now, the plastic mulching and drip irrigation area is increasing to reduce irrigation water and enhance crop yield. In this study, the soil water, salt, and nitrogen contents at the 0–100 cm soil layer under plastic mulching and non-mulching conditions with the surface irrigation—fertilizer broadcast practice and drip fertigation method were investigated at the maize elongation and maturation stages in the 2021 and 2022 seasons. The results show that the mulching practice and irrigation methods greatly influenced the soil salt and ionic nitrogen (NO3− and NH4+) distributions and, ultimately, the maize yield. Mulching reduced the soil salt content in the 0–20 cm soil layer by a mean of 35.7% under surface irrigation and by 18.6% under the drip irrigation condition. The NO3− content in the 0–20 cm soil layer with the drip fertigation system was approximately 8 times higher in mulching soil than that out of mulching. However under the surface irrigation condition, the NO3− content was 8–10 times lower under mulching than that out of mulching. The soil salt and NO3− contents were distributed uniformly at each soil layer deeper than a 40 cm depth, indicating minor effects of mulching. The soil NH4+ content decreased as the soil depth increased and distributed uniformly at each soil layer, indicating the insignificant influence of the mulching practice. As a result, the maize yield under the drip-mulching condition was approximately 11% (10.6~11.4%) higher than that under the surface-mulching condition in the two maize seasons. Given that surface irrigation is currently the primary irrigation method in the Hetao Irrigation District (HID), we have proposed three approaches aimed at enhancing maize production through the improvement of nitrogen levels in surface-mulching practices.

Effect of Soil Texture on Water and Salt Transport in Freeze—Thaw Soil in the Shallow Groundwater Area

Research on the variation in soil water, heat, and salt in unsaturated zones during the freeze–thaw process has great significance in efficiently utilizing water resources and preventing soil salinization. The freeze–thaw field experiment was carried out with the lysimeter as the test equipment to analyze characteristics of the soil freeze–thaw process, profile water content, main ion content, and salt content of three textured soils with the groundwater table depth of 0.5 m. The results showed that the soil temperature gradient and freezing depth were greater as the average soil particle size increased. The increment of water content at the depth of 0 to 30 cm in sandy loam and loamy sand decreased by 40.20~93.10% and 28.14~65.52% compared with that in sandy soil, and the average increment of salt content at the depth of 0 to 30 cm decreased as the average soil particle size increased during the freeze–thaw period. The average content of Ca2+, Na+, Cl−, and SO42− in loamy sand and sandy soil decreased by 4.37~45.50% and 22.60~70.42% compared with that in sandy loam at the end of the freeze–thaw period, and the correlation between soil salt content and water content decreased with the increase in the average soil particle size. The research results can provide a theoretical basis for soil salinization prevention and crop production in shallow groundwater areas.

The successive infiltration of various saline waters accelerates the infiltration processes and enhances the salt leaching in a coastal saline soil

AbstractThe local saline water resource has been widely used for soil water and salt managements in saline‐alkali area. The soil desalinization is strongly affected by the infiltration mode, and the melting saline ice infiltration can obtain soil salt leaching effectively. In this work, four melting sections (S1, S2, S3, and S4) were divided artificially according to the changes in meltwater from 5 (W5), 10 (W10), and 15 g L−1 (W15) ice. Various saline water samples of the above four sections with different salinities and volumes were prepared and infiltrated successively into soil columns that were packed with the coastal saline soils. The infiltration parameters, distribution patterns of soil moisture, salt, and sodium adsorption ratio (SAR), and soil desalinization in different sections were investigated and analyzed. Results showed that the infiltration of higher salinity water in the initial section increased the infiltration rates of slightly saline and fresh water in the last section. A greater infiltration rate, cumulative infiltration, and infiltration depth were ranked as W5 < W10 < W15. Moreover, the faster infiltration process obtained higher soil water contents throughout the S1, S1 + S2, and S1 + S2 + S3 sections, and more water was ultimately distributed in the deeper soil layer (S1 + S2 + S3 + S4 section). Both the soil salt and SAR increased initially (Section S1) and then decreased in the following sections; >80% of the total leached salt loads occurred in the S2 section for all treatments. Lower levels of soil salt contents and SAR developed within the later infiltration sections. Ultimately, the 30 cm desalinization layer was obtained among all treatments, and the treatments corresponding to the saline ice with higher salinity acquired lower salt contents and SAR values. These results indicate that the successive infiltration of water with various salinity levels, characterized by meltwater from saline ice, accelerated the infiltration process, and resulted in an obvious soil desalinization effect on the coastal saline soil.

Ridge tillage increased halophyte fine root production and turnover rates by altering soil properties in an abandoned farmland in northwest China

Ridge tillage is a common tillage practice used for farmlands and afforestation. However, the mechanisms by which ridges affect halophyte fine root dynamics in abandoned farmlands are still unknown. A field experiment was conducted to evaluate the effect of ridge tillage on root dynamics in an abandoned farmland over three consecutive years using a minirhizotron method. The rate of fine root production varied from 27 to 44 mm cm−2 each year, and the root turnover rate was between 7.46 and 16.99 times per year. Ridge tillage significantly decreased 0–1 mm diameter root production and root lifespan (28.98% and 19.77%, respectively) while increasing root mortality by 18.74%. Conversely, there was no significant effect of ridge tillage on roots within the 1–2 mm diameter range. Ridge tillage resulted in increased root production and root lifespan, which was mainly due to an increase in soil moisture. Clear seasonal patterns were observed for fine root production, root standing crop and root mortality due to increases in soil organic matter, soil water content and soil salt content in the abandoned farmland. Our results demonstrated that ridge tillage not only accelerated halophyte root production and lifetimes but also improved belowground productivity, providing a potential way to replant in the saline-alkaline soils of abandoned farmlands.

Estimating soil water and salt contents from field measurements with time domain reflectometry using machine learning algorithms

Soil water and salt contents are key soil physical parameters that play a crucial role in soil-related hydrological, ecological, environmental, and agricultural processes. Time domain reflectometry (TDR) is commonly used to measure in-situ soil water and salt contents, and provide possible solutions to quickly obtain soil bulk density (BD). However, the measurement accuracy is greatly influenced by the interaction of soil water and salt contents on the measured soil dielectric constant and electrical conductivity, especially for salinized soils. To accurately estimate the soil gravimetric (GWC) and volumetric (VWC) water contents, soil salt content (TS), and BD based on the TDR measurements, we designed different model input schemes to quantify the effect of different soil factors, and applied eight machine learning algorithms to map the non-linear relationship between model inputs and each target soil property. Results of a case study in Hetao Irrigation District in Northwest China indicated that soil particle-size fractions (psfs) are important inputs to predict all the above soil properties. Furthermore, BD mainly contributes to the prediction of soil GWC, and soil surface temperature (T) is effective in improving the GWC and TS estimations. Among eight machine learning algorithms used, extreme gradient boosting (XGB) and gradient boosting regression tree (GBRT) showed good robustness and strong learning capacity. It is recommended to apply XGB to precisely estimate GWC and BD, which resulted in the coefficients of determination (R2) of 0.80 and 0.69, respectively. On the other hand, GBRT precisely estimated the VWC and TS with R2 of 0.71 and 0.84, respectively. The evaluation of spatial distribution characteristic indicated that it is reliable to obtain the spatial distributions of the above soil properties from the TDR measurements based on the recommended model input schemes and machine learning algorithms.

Planning Spatial Layout of a Typical Salt Tolerant Forage of Sweet Sorghum in the Yellow River Delta via Considering Resource Constraints, Nitrogen Use Efficiency, and Economic Benefits.

In order to effectively address the issue of severe soil salinization in the coastal area of the Yellow River Delta, which has led to a significant number of medium and low-yield fields in this region, and to satisfy the rising demand for feed grain in China in recent years, a highly effective solution is to replace conventional crops by cultivating a specialized type of forage grass that can withstand high salinity levels and is well adapted to the local climate. This study proposed a spatial layout scheme for planting salt-tolerant forages, with the aim of providing a foundation for enhancing saline-alkali land and increasing resource utilization efficiency. The results showed that the climate conditions in the Yellow River Delta were suitable for planting sweet sorghum. With respect to soil salt content, the suitable planting regions for sweet sorghum can be classified into four categories: Suitable, moderately suitable, less suitable, and unsuitable, with soil salt concentrations of 2.62-5.25‱, 5.25-7.88‱, respectively. Concerning economic benefits, sweet sorghum's input-output ratio (74.4%) surpasses that of cotton in high saline-alkali zones, providing a significant advantage in comparison with traditional crops. In non-saline-alkali and light saline-alkali areas, the traditional winter wheat-summer maize planting system offers higher economic benefits and nitrogen use efficiency, so it is recommended to maintain this system as the dominant agricultural model. In moderately and severe saline-alkali zones, although one-season maize exhibits greater nitrogen efficiency, its economic benefits are lower than those of sweet sorghum. Hence, it is advisable to promote one-season maize in suitable regions and introduce salt-tolerant forage, such as sweet sorghum in other areas. This approach offers novel ideas and methods for crop spatial layout planning and addresses potential feed grain shortages in the region.

Temporal and Spatial Characteristics of Soil Salinization and Its Impact on Cultivated Land Productivity in the BOHAI Rim Region

Soil salinization can have an inhibitory effect on crop productivity and pose a serious threat to regional agricultural resource utilization and sustainable development. However, there are scarce studies on the quantitative impact of soil salinization on crop productivity. The purpose of this study is to identify the spatial and temporal characteristics of the cultivated land, the soil salinization degree, and the net primary productivity (NPP) of vegetation in the Shandong region around the Bohai Sea and to couple the quantitative relationship between soil salinization and the productivity of the cultivated land. We found that the amount of cultivated land in the study area gradually decreased from 2001 to 2019. The degree of soil salinization in the cultivated land in the north of the study area increased slightly from 2001 to 2005 and decreased continuously after 2011. The NPP value of the cultivated land increased, fluctuating from 2001 to 2019. The spatial distribution of the NPP value was generally lower in the north than in the south, with Dongying District as the boundary. In addition, in different soil salt content (g/kg) intervals, the change trends in cultivated land NPP varied. When the salt content of cultivated soil was in the range of 0–3 g/kg, 3–7 g/kg, or 7–15 g/kg, for every 1 g/kg increase in salt content, the NPP value decreased by 43.62 gC m−2a−1, 30.36 gC m−2a−1, and 44.19 gC m−2a−1, respectively. These results are expected to provide decision-making support for strengthening the dynamic monitoring and regulation of cultivated land salinization and promoting sustainable utilization of salinized cultivated land in the coastal areas to alleviate the food crisis.