The high amount of Electrical Conductivity (EC) in the groundwater is one of the major negative Geo-environmental problems which has a considerable effect on the quality of drinking water. To address this challenging problem we proposed an intelligent Machine Learning (ML) based approach to predict EC in urban areas. We applied the deep learning technique as one of the most applicable ML techniques with high capabilities for intelligent predictions. Five different deep neural networks (Net 1 to Net 5) were developed in this study and their reliability to predict EC with an emphasis on different settings of inputs, features, functions, and the number of hidden layers was evaluated. The achieved results showed that deep neural networks can predict EC parameters using minimum and economic input parameters. Results showed parameters Cl and SO4 with a high range of correlation and pH with a low range of Pearson correlation properties are influential parameters to be used as the input of neural networks. Activation function Relu, optimization function Adam with a learning rate of 0.0005 and loss function Mean Squared Error with the minimum of two hidden dense layers from Keras laboratory of Tensor Flow developed an efficient and fast network to predict the EC parameter in urban areas. Maximum epochs for developed networks were defined up to 2000 iterations while epochs are reducible up to 200 to drive minimum loss function outcome. The maximum training and testing R2 for developed networks was 0.99 in both the training and testing parts.

The aim of this study is to determine the amount of quantitative and qualitative changes in groundwater in the Sarvestan plain in south of Fars province, which is one of the critical plains in Iran in terms of water resources. In this research, zoning maps of electrical conductivity of water in GIS were prepared and various hydrochemical diagrams were illustrated. Different quality parameters of water resources were compared according to the statistical data collected and the experiments performed at the beginning of the 8-year period of the research. Chemical analysis of water samples shows that the groundwater type of most of the studied wells at the beginning of the period (2013) has changed from Ca-Cl and Mg-Cl types to Na-Cl type at end of the time period (2020). Determining the trend of chemical changes shows that the diversity of water samples in terms of anions and cations in water with increasing salinity at the end of the period is less than the variety of samples at the beginning of the period. According to the results of chemical experiments, evaporation, crystallization, and weathering of rocks are the factors that control the composition of groundwater in the study area. This study shows increasing the salinity of groundwater in addition to decreasing precipitation and high water use for agricultural application, due to the type of geological formations, especially the presence of salt domes at groundwater inlets to the plain on the east side of the study area.

Water scarcity, its necessity in food production, and environmental protection in the world have forced human beings to seek new water sources. Nowadays, application of unconventional water resources (wastewater) has been proposed in countries facing the crisis of water resources shortage; however, a few studies have dealt with this issue. The present study has evaluated the changes in the elements of the soil, irrigated with wastewater. For so doing, an experiment has been conducted on a randomized complete block design with three replications. Soil samples have been collected from the studied regions at two depths of 0-30 cm and 30-60 cm and the studied parameters have included sodium, total calcium, magnesium, some acidity, and electrical conductivity of the soil. Three regions of study (namely no irrigation, irrigation with treated wastewater, and irrigation with river waters) have been taken into consideration. Results have shown increased calcium, magnesium, and pH of the effluent from Zabol Wastewater Treatment Plant compared to the control; however, electrical conductivity and chloride have decreased in wastewater-irrigated soil. The electrical conductivity in the surface layer of wastewater samples, treated with an amount of 2.25 (ds/m), has had the most significant difference to the control and other treatments. It can be concluded that wastewater increases some soil properties, contributing to its restoration.

peer reviewed | The impact of climate change on water resource availability and soil quality is more and more emphasized under the Mediterranean basin, mostly characterized by drought and extreme weather conditions. The present study aims to investigate how electromagnetic induction technique and soil mapping combined with crop yield data can be used to optimize phosphorus (P) use efficiency by chickpea crop under drip fertigation system. The study was carried out on a 2.5-ha agricultural plot and the agronomic experiments in two growing cycles of chickpea crop. Soil spatial variability was first assessed by the measurement of soil apparent electrical conductivity (ECa) using the CMD Mini-Explorer sensor, and then, soil physicochemical properties were evaluated based on an oriented soil sampling scheme to explore other soil spatial variabilities influencing chickpea yield and quality. Data from the first agronomic experiment were used in geostatistical, multiple linear regression (MLR), and fuzzy c-means unsupervised classification algorithms to properly identify P drip fertigation management zones (MZs). Results from the Person's correlation analysis revealed that chickpea grain yield was more influenced by soil ECa (r = - 0.56), pH (r = - 0.84), ECe (r = - 0.6), P content (r = 0.72), and calcium (Ca) content (r = - 0.83). The proposed MLR-based model to predict chickpea grain yield showed good performances with a normalized root mean square error (NRMSE) of 0.11% and a coefficient of determination (R2) equal to 0.69. The identified MZs were verified by the one-way variance analysis for the studied soil and plant attributes, revealing that the first MZ1 presents a high grain yield, high soil P content, and low ECa. The low fertility MZ2 located in the south part of the studied site presented a low chickpea grain yield due to the low P content and the high ECa. Moreover, the application of P-variable rate fertigation regimes in the second field experiment significantly improved P use efficiency, chickpea grain yield, seed quality, and farmer income by 18%, 12%, 9%, and 136 $/ha, respectively, as compared to the conventional drip fertigation practices. The approach proposed in this study can greatly contribute to optimizing agro-input use efficiency under drip fertigation system, thereby improving farmers' incomes, preserving the ecosystem, and ensuring sustainable cropping systems in the Mediterranean climate.

Co-pyrolysis of sewage sludge and plastics have been utilized for producing biochars as a strategy to fix plastic pollution. However, comparative studies on the characteristics and environmental risk of heavy metals in biochars obtained by the co-pyrolysis of sludge and microplastic with/without metal additives are seldom. Here we demonstrated the effects of simulated co-pyrolysis (at 400 °C) of sewage sludge and metal-free or metal-loaded polyvinyl chloride (PVC) microplastics at different mass ratios (1:0, 19:1, 3:1, 1:3, sewage sludge: PVC (w/w)) respectively. Results revealed that co-pyrolysis of metal-loaded PVC and sewage sludge resulted in higher electrical conductivity, ash content, and an acidic pH of biochars as compared to the co-pyrolysis of metal-free PVC and sewage sludge. Addition of metal-loaded PVC increased total concentrations of calcium (Ca), magnesium (Mg), cadmium (Cd), and lead (Pb) in biochars, but reduced the bioavailability of Cd, chromium (Cr), nickel (Ni), and zinc (Zn) in biochars. Analysis of chemical speciation showed that heavy metals (except Pb) in biochars derived from co-pyrolysis of sewage sludge and metal-loaded PVC had higher percentage of more stable fraction (residual fraction) and lower potential ecological risk index (RI) value. S1AP3 (sludge: metal-loaded PVC = 1:3) biochar had the lowest environmental risk based on RI value (14.41). To sum up the present study suggests that the addition of metal-loaded PVC microplastic in sewage sludge had a positive impact on the immobilization of heavy metals during co-pyrolysis process.

The presence of microplastics (MPs) in freshwater systems that receive discharge of urban effluent implies a great environmental impact. In order to be able to generate proposals that solve this problem, it is necessary to know in detail the contributions of different MPs sources. The aim of this work was to study the contribution of urban sewage discharge to MPs pollution in a stream that runs through a medium-sized city. The spatial distribution of MPs with sizes between 100 μm and 1.5 mm present in surface water was measured and their characteristics, dimensions, shapes and identification were determined. Physical-chemical parameters of the stream water were measured, and a decrease in water quality was found due to wastewater treatment plants. The main source of MPs was effluent from the plants (97% of the total MPs), while the rest came from storm drains and discharge of tributaries. The maximum concentration of MPs found was around 72,000 MP/L (equivalent to 53 million MPs/s), at a point after discharge from both plants. Around 70% of MPs correspond to microfibers with a mean length of around 300 μm and a mean width of around 15 μm, and they are mainly polyethylene fibers. The remaining 30% of MPs are particles with lengths of around 140 μm. The transport of MPs between a point located after discharge of the plants and another point located about 3 km further on was studied, and no significant variation was found in the concentration of MPs. Electrical conductivity was used as a conservative tracer of MPs concentration. This work presents for the first time a detailed analysis of different contributions of MPs to a freshwater system in South America, which receives discharge of wastewater treatment plants, evidencing its important role in pollution.

Coastal wetland soils serve as a great C sink or source, which highly depends on soil carbon flux affected by complex hydrology in relation to salinity. We conducted a field experiment to investigate soil respiration of three coastal wetlands with different land covers (BL: bare land; SS: Suaeda salsa; PL: Phragmites australis) from May to October in 2012 and 2013 under three groundwater tables (deeper, medium, and shallower water tables) in the Yellow River Delta of China, and to characterize the spatial and temporal changes and the primary environmental drivers of soil respiration in coastal wetlands. Our results showed that the elevated groundwater table decreased soil CO₂ emissions, and the soil respiration rates at each groundwater table exhibited seasonal and diurnal dynamics, where significant differences were observed among coastal wetlands with different groundwater tables (p < 0.05), with the average CO₂ emission of 146.52 ± 13.66 μmol m⁻²s⁻¹ for deeper water table wetlands, 105.09 ± 13.48 μmol m⁻²s⁻¹ for medium water table wetlands and 54.32 ± 10.02 μmol m⁻²s⁻¹ for shallower water table wetlands. Compared with bare land and Suaeda salsa wetlands, higher soil respiration was observed in Phragmites australis wetlands. Generally, soil respiration was greatly affected by salinity and soil water content. There were significant correlations between groundwater tables, electrical conductivity and soil respiration (p < 0.05), indicating that soil respiration in coastal wetlands was limited by electrical conductivity and groundwater tables and soil C sink might be improved by regulating water and salt conditions. We have also observed that soil respiration and temperature showed an exponential relationship on a seasonal scale. Taking into consideration the changes in groundwater tables and salinity that might be caused by sea level rise in the context of global warming, we emphasize the importance of groundwater level and salinity in the carbon cycle process of estuarine wetlands in the future.

Urbanisation of riverine landscape is an increasing threat to the functionality of river ecosystems. In this study, we identify and classify macroinvertebrates indicator signature traits and ecological preferences.We hypothesised that urban pollution would differentially influence the distribution of macroinvertebrate traits and ecological preferences along a gradient of water quality deterioration. Hence, we identified and classified potential biological indicators traits and ecological preferences that were deemed tolerant of or sensitive to urban pollution gradient in the Niger Delta region of Nigeria. Physico-chemical variables (water temperature, depth, flow velocity, dissolved oxygen, biochemical oxygen demand, electrical conductivity (EC), nitrate, phosphate), and macroinvertebrates were collected from 2008 to 2012 seasonally during the wet and dry seasons once in a month in 11 stations in eight river systems. The results based on RLQ, fourth-corner and Kruskal-Wallis analyses indicate that traits/ecological preferences such as tegumental/cutaneous respiration, cased/tubed body armouring, a preference for silty water, bivoltinism, burrowing and a high tolerance for oxygen depletion, were statistically significantly associated with the heavily impacted stations. These traits were positively correlated with physico-chemical variables such as EC, nitrate and phosphate indicative of urban pollution. On the other hand, traits/ecological preferences such as permanent attachment, crawling, swimming, univoltinism and a moderate sensitivity to oxygen depletion were associated with the least impacted stations and were negatively correlated with physico-chemical variables indicative of urban pollution. Overall, the observed differential responses of traits and ecological preferences to urban pollution along a gradient of water quality impairment suggest that traits and ecological preferences can serve as useful biological indicators and thus supports the growing evidence of the utility of the trait-based approach.

Soil microbes influence the uptake of toxic metals (TMs) by changing soil characteristics, bioavailability and translocation of TMs, and soil health indicators in polluted environment. The potential effect of Streptomyces pactum (Act12) and Bacillus consortium (B. subtilis and B. licheniformis; 1:1) on soil enzymes and bacterial abundance, bioavailability and translocation of Zn and Cd by Symphytum officinale, and physiological indicators in soil acquired from Fengxian (FX) mining site. Act12 and Bacillus consortium were applied at 0 (CK), 0.50 (T1), 1.50 (T2), and 2.50 (T3) g kg⁻¹ in a split plot design and three times harvested (H). Results showed that soil pH significantly dropped, whereas, electrical conductivity increased at higher Act12 and Bacillus doses. The extractable Zn lowered and Cd increased at each harvest compared to their controls. Soil β-glucosidase, alkaline phosphatase, urease and sucrase improved, whereas, dehydrogenase reduced in harvest 2 and 3 (H2 and H3) as compared to harvest 1 (H1) after Act12 and Bacillus treatments. The main soil phyla individually contributed ∼5–55.6%. Soil bacterial communities’ distribution was also altered by Act12 and Bacillus amendments. Proteobacteria, Acidobacteria, and Bacteroidetes increased, whereas, the Actinobacteria, Chloroflexi, and Gemmatimonadetes decreased during the one-year trial. The Zn and Cd concentration significantly decreased in shoots at each harvest, whereas, the roots concentration was far higher than the shoots, implicating the rhizoremediation by S. officinale. Accumulation factor (AF) and bioconcentration ratio (BCR) of Zn and Cd in shoots were lower and remained higher in case of roots than the standard level (≥1). BCR values of roots indicated that S. officinale can be used for rhizoremediation of TMs in smelter/mines-polluted soils. Thus, field trials in smelter/mines contaminated soils and the potential role of saponin and tannin exudation in metal translocation by plant will broaden our understanding about the mechanism of rhizoremediation of TMs by S. officinale.

The current study was conducted to (1) examine seasonal and spatial distribution of heavy metals and metalloid in sediment from the Saigon River and (2) apportion and quantify their pollution sources. Ninety-six sediment samples were taken in the rainy and dry season on 13 sampling sites, distributed over the lower reaches of the River, to analyze for exchangeable concentration of 11 heavy metals and metalloid (Al, B, Cd, Co, Fe, In, Mn, Ni, Pb, Sr, and Zn), pH, EC, organic carbon content, and particle-size distribution. Generally, the concentration of 11 elements was ranked in the order Mn > Al > Fe > Zn > Sr > In > B > Ni > Co > Pb > Cd. Hierarchical cluster analysis grouped 13 sampling sites into two parts based on the similar concentration of the 11 elements. Three-way analysis of variance showed that the total exchangeable concentration of 11 elements was significantly higher in the rainy season than in the dry season and in the upper part than in the lower part of the river. Principal component analysis/factor analysis and correlation analysis revealed that three pollution sources (PS) may contribute to enriching the 11 examined elements in the sediment. These sources included (PS1) from catchment through water erosion over natural areas, explaining 83%, (PS2) mixed sources from catchment through water erosion over agricultural fields and inside Ho Chi Minh City, accounting for 6%, and (PS3) mixed sources from lowland areas, explaining 7.8% of the total variance of the elements. In brief, the sediment concentration of 11 metals and metalloid varied with season and space and three major pollution sources from river catchment, inside Ho Chi Minh City, and lowland contributively enriched the elements in the sediment of the River.