Soil Salinity Management Research Articles

Driving Factor Identification for the Spatial Distribution of Soil Salinity in the Irrigation Area of the Syr Darya River, Kazakhstan

Soil salinization has become a worldwide issue affecting agricultural development. Statistical methods and spatial analysis were used to analyze the degree and type of saline soils and their spatial distribution. The driving factors of soil salinity were explored using Geodetetcor models. In this study, 84 soil samples were collected from a 0–20 cm soil layer, and the total salt concentration and salt ion composition were measured. The results of statistical analysis and cluster analysis showed that SO42− and Ca2+ had the highest concentrations of salt ions in terms of anion and cation contents, respectively. The interpolation results indicated that the study area was dominated by mild saline soils, with sulfate-type saline soils and chloride-sulfate-type soils dominating. Results of the factor detector suggested that the distance to the irrigation system (0.425), and distance to the drainage system (0.42), explained salinity more strongly in the Shardara district, and elevation (0.326) was the most important influencing factor for salinity in the Mahtaaral district. Results of the interaction detector indicate that human factors (distance to irrigation canals ∩ distance to drainage canals) had a stronger explanation both in the Shardara and Mahtaaral districts. This research provides a scientific basis for soil salinity regulation and management, which is crucial for sustainable agricultural development.

Comparative effects of different kinds of biochar on ammonia volatilization and chemical properties of saline soil

ABSTRACT The study was established to examine the effect of three biochar types (orange peels biochar (OPB), sorghum panicles biochar (SPB), and wood chips biochar (WCB)) prepared at low temperature (270 °C) added at four doses (0, 1, 3, and 6% w/w) on ammonia (NH3) volatilization and chemical characteristics of a saline soil treated with urea. The results revealed that treating the saline soil with different biochar types at all doses caused a significant reduction of cumulative NH3 volatilization compared to the unamended soil. The effectiveness of biochar types in decreasing NH3 volatilization from this soil was: WCB > SPB > OPB > unamended soil. Soil pH decreased significantly with applying different types and doses of biochar. Treating the saline soil with 3% each of SPB and WCB and 6% WCB decreased electrical conductivity significantly in the soil extract compared to the unamended soil. The sodium adsorption ratio decreased significantly with applying SPB and WCB at 3 and 6%. The biochar produced at a low temperature was found to have an acidic effect. Accordingly, biochar applications are currently one of the most promising technologies and practices for rehabilitation and sustainable management of saline soils as well as mitigating climate change.

Desalinization effect of simulated cut‐soiler‐based residue filled preferential shallow subsurface drainage: Improvement of physiology and yield of rain‐fed pearl millet in saline semiarid regions

AbstractSoil salinity is a major soil degradation problem that limits agricultural production. The cut‐soiler constructed preferential shallow subsurface drainage (PSSD) method is a promising salinity management technology for small‐scale application and adoption in drylands. This study assessed the effectiveness of rice residue‐filled PSSD in managing soil salinity and its effect on the physiology and yield of pearl millet. The cut‐soiler simulated drains were constructed manually in semi‐controlled lysimeter. A double replicated, split–spilt plot experiment, comprising with and without cut‐soiler drainage (main‐plot), two soil types (sub‐plot) and three irrigation water salinity (4, 8, 12 dS m−1) (sub‐sub plot) were conducted during 2019–2020. The cut‐soiler PSSD reduced ~60% soil salinity after 2 years. The PSSD reduced soil salinity by 23.28 and 41.46% in April 2019 and April 2020 (before pearl millet sowing). This reduction was 32.24 and 46.23% in October 2019 and 2020 (at harvest). Cut‐soiler drainage (PSSD) areas recorded lower soil moisture (%) indicated greater outflow of water and salinity. The salinity Inhibition efficiency increased upto 2 years of construction and then decline. The pearl millet grain and biological yields were improved by 23.54 and 12.64%, respectively and a positive effect on plant water relations and physiology was observed. The cut‐soiler PSSD was found to enhance salt removal and reduce salt accumulation under saline water irrigation. These drains can be constructed in a single farm operation at individual farm levels. Therefore, it could be a potential alternative for soil salinity management in semi arid regions irrigated with saline groundwater.

Inversion of Soil Salinity Using Multisource Remote Sensing Data and Particle Swarm Machine Learning Models in Keriya Oasis, Northwestern China

Soil salinization is a global problem that damages soil ecology and affects agricultural development. Timely management and monitoring of soil salinity are essential to achieve the most sustainable development goals in arid and semi-arid regions. It has been demonstrated that Polarimetric Synthetic Aperture Radar (PolSAR) data have a high sensitivity to the soil dielectric constant and soil surface roughness, thus having great potential for the detection of soil salinity. However, studies combining PALSAR-2 data and Landsat 8 data to invert soil salinity information are less common. The particle swarm optimization (PSO) algorithm is characterized by simple operation, fast computation, and good adaptability, but there are relatively few studies applying it to soil salinity as well. This paper takes the Keriya Oasis as an example, proposing the PSO-SVR and PSO-BPNN models by combining PSO with support vector machine regression (SVR) and back-propagation neural network (BPNN) models. Then, PALSAR-2 data, Landsat 8 data, evapotranspiration data, groundwater burial depth data, and DEM data were combined to conduct the inversion study of soil salinity in the study area. The results showed that the introduction of PSO generated a satisfactory estimating performance. The SVR model accuracy (R2) improved by 0.07 (PALSAR-2 data), 0.20 (Landsat 8 data), and 0.19 (PALSAR + Landsat data); the BP model accuracy (R2) improved by 0.03 (PALSAR-2 data), 0.24 (Landsat 8 data), and 0.12 (PALSAR + Landsat data), and then combined with the model inversion plots, we found that PALSAR + Landsat data combined with the PSO-SVR model could achieve better inversion results. The fine texture information of PALSAR-2 data can be used to better invert the soil salinity in the study area by combining it with the rich spectral information of Landsat 8 data. This study complements the research ideas and methods for soil salinization using multi-source remote sensing data to provide scientific support for salinity monitoring in the study area.

English

The field experiment were performed on the site of Werer Agricultural Research Center (Ethiopia)  to study optimal irrigation scenario by taking in to account the leaching requirement and drainable excess water for three successive years. Six irrigation treatments were evaluated at different growth stages of onion plant namely at initial growth stage four irrigation event  23 mm (T1), 16.2 mm (T2) 21.0 mm (T3), 13.8 mm (T4), 27.0 mm (T5), 19.8 mm (T6), at development growth stage five irrigation event 32.4 mm (T1), 23.4 mm (T2), 28.8 mm (T3), 19.2 mm (T4), 36.6 mm (T5), 27.0 mm (T6), at mid growth stage four irrigation event 53.4 mm (T1), 37.2 mm (T2), 48.0 mm (T3), 31.8 mm (T4), 60.6 mm (T5), 44.4 mm (T6), and at late stage two irrigation event 58.0 mm (T1), 40.8 mm (T2), 53.4 mm (T3), 35.4 mm (T4), 67.2 mm (T5), 49.2 mm (T6) applied respectively. The irrigation amount and amount of water added for leaching had no significant difference on onion bulb diameter and bulb length across the years. The highest marketable yield (21784 kg/ha) and water use efficiency (1.89 kg/m3) were recorded at the first year. The maximum bulb diameter were recorded from T6 (5.41 cm) and the lowest recorded from T2 (4.81 cm). Treatment T2 were recommended for the production of onion at middle awash. The developed optimal irrigation scheduling and drainable excess water can be used as a guide to yield potential allocation decision related to soil salinity management.  Key words: Drainage, optimal, leaching, onion.   

Soil salinity: A global threat to sustainable development

AbstractSoil is a vital resource for feeding the burgeoning global population, and it is also essential for realizing most of the ‘United Nations Sustainable Development Goals (SDGs)’. For example, it is vital to realizing the ‘Zero hunger (SDG2), Good health and well‐being (SDG3), Clean water and sanitation (SDG6), and Life on land (SDG15)’. Excess salts present in the soil make it saline, and it poses a significant threat to agricultural production and environmental health. Soil salinity is an extensive problem and spreads over one billion hectares extended over 100 countries. This paper presents a comprehensive review of global soil salinity management through the applications of remote sensing and GIS. All possible sources of relevant and current literature were accessed and more than 260 publications were collected and carefully analysed, for this review. The rationale and severity of the salinity problem are provided. The impact of salinity on plant yield and the effect of climate change on soil salinity are detailed. The salinity indicators and salinity monitoring and mapping are provided, and the global cases of soil salinity management through remote sensing and GIS applications under different agro‐hydro‐climatic environments are discussed, followed by a summary of conclusions and challenges along with future research directions. The analysis of past investigations showed that remote sensing strategy might be a practical approach to adequately assess plant response such as evapotranspiration under diverse salinity environments, yet it additionally has various difficulties. The lower spatial and temporal resolution of imagery may reason errors because of subpixel heterogeneity. However, with the improvement of the better‐resolution thermal infrared remote method, there is the possibility to spot spatial variations at a smaller scale.

The knowledge levels, perceptions, and practices of irrigation farmers in the context of soil salinity management in the South African sugarcane industry*

AbstractSoil salinity is a well‐researched issue. However, farmers' knowledge and perceptions of salinity management are less known. A questionnaire survey was conducted with 34 sugarcane growers, farming 18,174 ha under irrigation in South Africa. The questionnaire evaluated current knowledge levels, management practices, and perceptions about salinity management.The results reveal several knowledge gaps. Many farmers were not monitoring their soil salinity status or the water quality used for irrigation. A large portion (71%) of farmers observed visible signs of salinity; however, very few were implementing flushing of salts with irrigation. Contrastingly, participants suggested that they perceived the threat of salinity and have sufficient knowledge about causes and the preventative and corrective measures for salinity management. In addition, respondents were satisfied that the benefits of salinity management outweigh the costs. Participants, however, perceived practical difficulty and hassle factors relating to the knowledge and skill required for implementation. In conclusion, extension activities need to extend beyond knowledge sharing to the level of implementation. On‐farm testing, demonstration plots, farm visits, and technical tours are recommended. Relevant economic and practical case study information must be gathered and shared with larger farmer groups.

Evaluating the impacts of saline water irrigation on soil water-salt and summer maize yield in subsurface drainage condition using coupled HYDRUS and EPIC model

Field experiment combined with numerical simulation is an efficient approach for evaluation the effects of saline water irrigation on soil water-salt movement, crop growth and water productivity. In this study, HYDRUS model was coupled with EPIC module to evaluate the effects of saline water irrigation on soil salinity and grain yield under subsurface drainage condition. Two years’ field experiment data collected in lysimeters of summer maize irrigated with water of two different levels of salinity under different subsurface drain depths was used to calibrate and validate the coupled model. The coupled model was then adopted to evaluate the effects of salinity stress on evaporation, transpiration and water productivity (WP) and of long-term saline water irrigation on soil salinity and grain yield under subsurface drainage. Results indicated that simulated values of soil water-salt content, subsurface drainage amount and concentration, grain yield and evapotranspiration (ET) were in good agreement with observed values. Transpiration and WP were reduced by salinity stress, while evaporation was sensitive to drain depth. Soil salinity evidently increased when irrigation water salinity was higher than 4.0 dS m−1 in each simulated year under drain depth of 80 cm. Grain yield maintained at around 7600 kg ha−1 when water salinity is 4.4 dS m−1 under drain depth of 80 cm, and decreased with higher water salinity across all simulated years. There were significant exponential relationships between soil salinity, grain yield and irrigation water salinity in the long-term simulation. Thus, the appropriate irrigation water salinity should be 4.0–4.4 dS m−1 under subsurface drain depth of 80 cm in the present study. The combined application of saline water irrigation and subsurface drainage should be given more attention for long-term soil salinity and grain yield management in the future.

Soil salinity management using a Field Monitoring System (FMS) in tsunami-affected farmlands in Miyagi, Japan

Soil salinity management using a Field Monitoring System (FMS) in tsunami-affected farmlands in Miyagi, Japan

A modelling approach and module for salinity management in drip irrigation

The article describes a new modelling approach and module for soil salinity management. The two major objectives of the module are to simulate the seasonal course of the salinity of the soil solution in the active root zone of drip-irrigated crops to assist irrigators to optimise irrigation and salt leaching, and to help evaluate the salt fluxes in the deep percolating water for assessing the longer-term salt load of the irrigated crops on the regional ground and surface water resources. The module is based on the solutions of the DIDAS program for quasi-steady water flow and uptake for various drip irrigation scenarios, and on differentiating the applied water to evaporation from the soil surface, uptake by the plant roots, deep percolation through the root zone that leaches salt out of it, and deep percolation outside of the root zone that does not leach salts. After laying out the rationale behind the suggested approach and outlining the expressions used in the module for evaluating the salinity of the root zone, several sample computations, in silico experiments, are performed to illustrate the module functionality and its potential application, and to serve for sensitivity analysis of the system parameters. Additional investigation is needed into the adequacy of the suggested modelling approach and the developed module to simulate soil salinity in the active root zone. • The module evaluates seasonal courses of root zone salinity in drip-irrigated fields. • It simulates root system development but does not predict plant growth and yields. • It is based on modelling quasi-steady water flow and uptake and salt mass balance. • The deep percolating water are partitioned into two fractions. • One that flows through the root zone and leaches salt out of it, and one that flows around it.

SALEACH: A new web-based soil salinity leaching model for improved irrigation management

Leaching is essential in irrigated croplands where natural precipitation is insufficient to control salinity buildup. Several useful models exist for salinity management; however, leaching requirement (LR) calculations are based on steady-state approaches that only consider salinity tolerance of crops and irrigation water salinity to estimate the LR. In this study, a web-based soil salinity leaching management model (SALEACH) was developed as an online tool to assist growers for better and easier management of soil salinity to sustain agricultural production in irrigated croplands. SALEACH employs the traditional steady-state approach to estimate LRs but improves outputs by not only considering irrigation water salinity (ECiw) and salinity tolerance of specific crops (ECt), but also root water uptake patterns to account for irrigation system differences, and soil types for differences in hydraulic characteristics, as well as water stress and rainfall input. The SALEACH model can calculate the required irrigation water depth by using the estimated LR or any user-specified leaching fraction (LF) values; it can predict the drainage water salinity and soil salinity in the rootzone based on the applied leaching; and it can estimate relative crop yield for a given LF. SALEACH-estimated LRs were assessed in different soil types and irrigation systems by comparing them with LRs, soil water and drainage water salinity values obtained from an existing steady-state model (WATSUIT) and a transient-state model (HYDRUS-1D). Statistical analyses showed that SALEACH-estimated LRs, soil salinity, and drainage water salinity were all in the acceptable ranges of the corresponding values derived from other models. Thus, we conclude SALEACH is reliable and can be employed by practitioners to produce satisfactory estimations of LRs and soil salinity by considering the soil, crop, water quality, and irrigation system. Adoption of the model can improve water use efficiency and reduce groundwater pollution.

Socioeconomic, biophysical, and environmental impacts of raised beds in irrigated wheat: A case study from Egypt

Raised beds (RB) are hailed as means to mitigate the problem of excessive irrigation. However, their adoption and impacts in Egypt are not well-documented. This paper is based on survey data collected from a sample of 691 wheat fields drawn from three major wheat-producing provinces of Egypt. Using area-weights for upward aggregation, we estimated that 19.3% of total wheat area in the three provinces is cultivated with raised beds. We applied the endogenous switching regression model to analyze the socioeconomic, biophysical, and environmental impacts of RB. Model results showed that the adoption of RB led to a 937 kg/ha (12.79%) increase in yield, a US$77.60/ha (9.47%) increase in gross margins, an 824.63 m3/ha (15.05%) reduction in irrigation water application, 16.7% reduction in seeding rate, 5.56% increase in water productivity, and an 11.80% reduction in downside yield risk. Adoption of RB didn’t have significant effect on soil salinity and quantities of fertilizer and labor inputs. These results show that RB can provide panacea to several interrelated socioeconomic, biophysical, and environmental problems associated with irrigation. The policy implication of our findings is that Egypt and other similar countries can benefit from embracing RB as part of the technology packages promoted by their national agricultural extension systems. The benefits to these countries will increase if they invest more on research for adapting and perfecting the RB technology including its mechanization and its efficacy in soil salinity management.

Identifying coastal saline soil management practices to reduce land degradation and increase crop production in Bangladesh

A consecutive three year duration field experiment was carried out to identify which of a suitable mulch material and a planting bed or their combinations potentially reduce salt accumulation in soil and increase snake gourd yield in coastal saline soils. There were nine treatment combinations having three kinds of mulch materials: no mulch (control), rice straw mulch and plastic mulch, and three kinds of planting beds: convex bed, flat bed and concave bed. Plastic mulch reduced electrical conductivity of soil by 32% and increased soil temperature by 23% and gravimetric soil moisture content by 25% over control treatment. Plastic mulch had a fruit yield of 30.73, 28.06 and 26.32 t ha-1, which was 72, 237 and 268 % higher than control treatment in 2018, 2019 and 2020, respectively. The convex bed planting had significantly higher fruit yield than flat bed and concave bed planting. Plastic mulching and convex bed planting may therefore be recommended for reducing soil salinity and improving snake gourd yield in coastal saline regions.
 Journal of Bangladesh Academy of Sciences, Vol. 44, No. 2, 145-159, 2020

Crop and Residue Management Improves Productivity and Profitability of Rice–Maize System in Salt-Affected Rainfed Lowlands of East India

This study was conducted over 3 years in a salt-affected coastal rainfed lowland ecosystem. Farmers most commonly grow tall rice varieties in the wet season to cope with flash and/or stagnant floods, leading to large amounts of rice residue production. Most of the land remains fallow during the dry season because of increased salinity and scarcity of freshwater for irrigation. The study aims to provide options for increasing cropping intensity through management of crop residues (CR) and soil salinity, conservation of soil moisture, and reduction in production cost. The rice–maize rotation was assessed with rice as the main plot as (1) puddled transplanted rice (PTR) with CR of both rice and maize removed, (2) PTR and 40% CR of both crops retained, (3) dry direct-seeded rice (DSR) with CR of both crops removed, and (4) DSR with 40% CR of both crops retained. Maize in the dry season was supplied with different N levels as sub-plots—control (0 kg N ha−1), 80, 120, and 160 kg N ha−1. DSR, when combined with CR retention (DSR + R), reduced soil salinity. The increase in rice grain yield with CR retention (observed in second and third years) and crop establishment (higher in DSR versus PTR in the third year) was 16 and 24%, respectively. The cost of production increased by 17% (USD 605 ha−1) in PTR compared with DSR (USD 518 ha−1). CR retention reduced irrigation water requirement by 37% and N requirement by 40 kg ha−1 for hybrid maize. When CR was removed (−R), the N requirement for hybrid maize increased to 160 kg N ha−1 compared to when it was partially (40%) retained, where the requirement was 120 kg ha−1 with similar yields. Available N was highest under DSR + R (314 kg ha−1) and lowest under PTR − R (169 kg ha−1), and it also increased with increasing N application up to 120 kg ha−1 (+R) and 160 kg ha−1 (−R). The results of the study hold promise for increasing cropping intensity and farmers’ incomes, with broader implications for increasing productivity on about 2.95 million hectares currently under a rice–fallow system in eastern India, and in coastal areas affected by similar conditions in South and Southeast Asia.

Management of soil salinity associated with irrigation of protected crops

Long-term evaluation of soil chemical changes in the soil is required to optimize irrigation of protected crops and to control associated environmental issues. In this study, the multi-component solute transport module UNSATCHEM of HYDRUS-1D was used to assess the effects of long-term (2018–2050) irrigation on salt build-up in the soil under unheated greenhouse conditions. Blended water (recycled water, artificially recharged groundwater and harvested rainwater) was used to irrigate tomato, cucumber, capsicum, and eggplant. Irrigation management included four leaching fractions (LF), i.e., accounting for 0, 15, 20, and 30% of applied excess water. The effects of four amounts of annual gypsum application, i.e. 0, 1.7, 2.6, and 3.4 t/ha, were also simulated.Model-simulated annual root water uptake by cucumber, tomato, capsicum, and eggplant was 303, 476, 642, and 649 mm, respectively, for an irrigation schedule based on outdoor temperature thresholds. Annual drainage was 4.1–6.1% of irrigation for these crops. Average salinity in the soil solution (ECsw) at the end of the simulation (year 2050) reached 6.5 dS/m for cucumber, 7.6 dS/m for tomato, 8.7 dS/m for capsicum, and 9.3 dS/m for eggplant. Soil salinity was building up at a nearly constant rate over 33 years. Exchangeable sodium percentage (ESP) at the end of the simulation was 30.8% for tomato, 27.1% for capsicum, 33.2% for eggplant, and 31.4% for cucumber. These results indicate that both salinity and sodicity will exceed critical threshold values and thus must be managed to maintain sustainability of irrigated horticulture. Modeling showed that higher irrigation (up to 15–20%) coupled with an annual addition of gypsum of 1.7 t/ha kept both salinity and sodicity (SAR, ESP) below critical thresholds while pH was reduced from 8.7 to 7.8, thus creating a favorable soil environment for long-term sustainable vegetable production under greenhouse conditions. The new gypsum application module implemented in the UNSATCHEM model has broad applicability in evaluating soil amendment scenarios to address sodicity hazards linked to long-term irrigation.

Spatial Prediction of Soil Salinity in a Semiarid Oasis: Environmental Sensitive Variable Selection and Model Comparison

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.

Analyzing spatiotemporal characteristics of soil salinity in arid irrigated agro-ecosystems using integrated approaches

Soil salinization is one of the most common land degradation processes that impacts agricultural production, environmental health, and economic welfare. The first task in managing soil salinity is to understand its spatiotemporal characteristics, causal factors and influences, both over large regions and within individual fields. In this study, a typical irrigated agro-ecosystem located in the upper Yellow River basin, suffering from long-term soil salinization problems, was selected as the case study area. Field sampling experiments and investigations related to soil layer salt content, groundwater, irrigation and ground elevation were carried out at three scales (field scale, canal scale and regional scale) covering both croplands and natural vegetation patches during 2016 and 2017. Spatiotemporal characteristics of soil salinity were analyzed for the three scales based on sampling data, remote sensing, geostatistical analysis and model simulation. Results showed that, at the regional scale, the soil salinity distribution was dominated by topography and groundwater depth; at the canal scale, it was dominated by irrigation and cropping pattern; at the field scale, it was dominated by micro-topography and the uniformity of field irrigation. Scale-dependent soil salinity management strategies should be adopted to maintain agricultural production and the sustainability of natural ecosystems. It can be concluded that using integrated approaches including multi scale soil sampling, model simulation and other modern techniques is an effective way for thorough understanding and management of soil salinity.

Soil physical and chemical properties and drain water quality as affected by irrigation and leaching managements

ABSTRACT Saline-sodic soils commonly display a poor soil structure which is associated with the reduction in soil quality. Therefore, optimal management of soil and water salinity in saline-sodic soils should be regarded as an important factor in sustainable agriculture. The main purpose of the current study was to address the combined effect of irrigation and leaching managements on soil physical and chemical properties and drain water quality. Treatments including three irrigation water qualities, ECi = 0.6, 3 and 6 dS/m, two irrigation managements and three irrigation durations (8, 45 and 100 days). Two irrigation managements included intermittent irrigation at the depletion of 30% field capacity (M1) and daily irrigation with leaching fraction of 0.15 (M2) both followed by heavy leaching. Heavy leaching tests were applied on soil columns after 16, 56 and 114 days. The results showed that irrigation management and duration of the irrigation were found to be much more effective on infiltration, while irrigation water quality had a minor effect. The results revealed that final infiltration capacity under the daily irrigation was higher than the intermittent irrigation. Daily irrigation could control the salt until the medium water quality (ECi = 3 dS/m) and its soil chemical properties were similar to the intermittent irrigation. Daily irrigation had the most effect on EC control of soil and consequently on EC reduction of cumulative drain water compared to the intermittent irrigation. Reduced salinity by heavy leaching under the daily irrigation was more than intermittent irrigation. Under the intermittent irrigation, heavy leaching has increased the soil sodium adsorption ratio compared to the daily irrigation. Overall, under the daily irrigation, the soil physical and chemical properties were more suitable than the intermittent irrigation. According to the results, the intermittent irrigation is recommended in the areas where there are water resource limitations.

Effect of organic amendments on soil salinity and the growth of maize (Zea mays L.)

Soil salinity is a major concern in southwestern part of Bangladesh because almost 30% cultivable lands are currently lying under risk of salinity where 30-50% yields loss is happening. Organic amendments have found to be effective in the amelioration of saline soil by improving soil physical and chemical properties as well as crop selection is another criteria for sustaining viability of crops in saline soil. For ensuring sustainable saline soil management, a comparative pot study was carried out during kharif 1 season in 2015 to observe the effect of organic amendments (solid waste, vermicompost and cow dung) on soil salinity and its influence on the growth of maize. Composite soil was collected at a depth of 0-15 cm from Gozalmari village of Jalma Union in Batiaghata Upazila under Khulna district, Bangladesh that was saline (10.6 dS/m) in nature and the irrigation water sample was collected from beside Kazibacha river (4.28 dS/m) that was also moderately saline. The maize cultivar “Shuvra” was used for cultivation in the study. The experiment comprised of four treatments viz. T0: Control (No organic manure); T1: Solid waste (36g); T2: Vemicompost (72g); T3: Cow dung (33g). Five seeds were sown in each pot. Seeds were treated with Agrosan GN to protect them from seed and soil borne pathogens. Chemical fertilizers were not used in the experiment. Irrigation was done two times before harvesting: at 20 days after sowing (DAS) and at 40 DAS with river water and rain water was irrigated naturally during the season. Findings were that the organic amendments significantly influence the physico-chemical properties of the saline soil. All organic treated soils significantly reduce the soil EC (from 10.6 dS/m to 3.4 dS/m) and pH (from 7.63 to 7.38) compared to control soil (p?0.05). In case of survival parameters (e.g %gemination, rate of survival at 50 DAS) of maize, the treatments were found insignificant (p?0.05). But in terms of growth parameter (plant height and root length), significant differences were found between control and organic amendments treated soil (p?0.05). It may be concluded that organic amendments treated soils showed better results than that of control soil. If proper management can be implemented, this positive results will bring hope to the local poor farmers at least can introduce a new crop in fallow agricultural land during the kharif 1 season.

Using proximal sensor data for soil salinity management and mapping

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.