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.

An investigation into the pollution of stormwater runoff from automobile workshops in Nigeria was performed. Also, multivariate regression was used to predict the pH, oil, and grease (O&G) as well as the electrical conductivity (EC) in relation to the characteristics of the solids and metals pollutants of the untreated automobile workshop stormwater. The results indicated that automobile workshops contributed notable amounts of pollutants to stormwater runoff. Results were compared with Nigerian and USEPA standards. It was found that most of the parameters had mean value ranges far greater than standard limits. The multivariate regression showed variations in the results obtained from different automobile workshops. These variations could be due to the influence of factors such as the volume of automobile servicing activities and the waste generated from these activities that flow in the stormwater runoff. However, the bulk of the EC and pH of the stormwater were associated with the concentrations of the total dissolved solids and copper while the bulk of the O&G concentration was associated with the concentrations of lead and cadmium. It is recommended to treat automobile workshop stormwater to prevent detrimental effects in aquatic systems. Future research is aimed at modeling such treatment using multivariate regression techniques is warranted.

This study investigates the incidence of MPs in surface sediment samples, collected from the Anzali Wetland, Gillan province, North of Iran. This natural habitat receives municipal wastewater effluents and hosts industries and recreational activities that could release plastic to the wetland. There is need for studies to understand MPs pollution in wetlands. A total of 40 superficial sediment samples were taken covering potential pollution hotspots in the wetland. The average level of MPs was 362 ± 327.6 MP/kg: the highest MPs levels were near the outlet of a highly urbanized river (Pirbazar River) (1380 MP/kg), which runs through Rasht city. This was followed by 1255 MP/kg where there was intense fishing, boating and tourism activities in the vicinity of Bandar-e Anzali city. Fibers were the most common type of MPs (80% of the total MPs detected). The MPs polluting the wetland were predominantly white/transparent (42%), and about 40% of them were >1000 μm. Polypropylene (PP) and polyethylene (PE) prevailed in MPs found. MPs were characterized with polarized light microscopy, Raman spectroscopy, Scanning Electron Microscopy coupled with Energy-Dispersive X-ray spectroscopy. Microplastics levels were found to correlate significantly (p > 0.7) with electrical conductivity (EC) and sand-size fraction of the sediments. Coarse-grained sediments presented large capacity to lodge the MPs. This study can be used to establish protection policies in wetlands and newly highlights the opportunity of intercepting MPs in the Anzali Wetland, which are generally >250 μm, before they fragment further.

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.

Constructed wetlands (CWs) inoculated with exogenous microbes have great potential for removing pollutants in adverse environments. The rapid loss of functional bacteria and the high cost of repeated additions of inoculum, however, limit the practical application of this technology. In this study, C–F2 immobilized bacteria (i.e., immobilized salt-tolerant bacterium Alishewanella sp. F2 incorporated with a carbon source) were developed and utilized in CWs for solving the above problems. A 60-day experiment demonstrated that bioaugmented CWs (Bio-CWs) with the addition of C–F2 immobilized bacteria into the bottom gravel layer of CW microcosms (B-CF2 treatment) exhibited high nitrogen removal efficiency under a saline condition (electrical conductivity of 15 mS/cm). We measured mean nitrate nitrogen (NO₃⁻-N) and total nitrogen (TN) removal percentages of 97.8% and 88.1%, respectively, which were significantly (p < 0.05) higher than those in Bio-CWs with microbial inoculum (MI-F2 treatment, 63.5% and 78.2%) and unbioaugmented CWs (CK, 48.7% and 67.2%). The TN content of the entire plant was significantly (p < 0.05) increased in B-CF2 (636.06 mg/microcosm) compared with CK (372.06 mg/microcosm). The relative abundances of the genera Alishewanella (i.e., the exogenous bacterium, 5.5%), Clostridium-XlVa (8.8%) and Bacteroides (21.1%) in B-CF2 were significantly (p < 0.05) higher than in MI-F2 and CK, which improved the denitrification capacity of CWs. Overall, a high denitrification efficiency and durability were achieved in the newly developed Bio-CWs (i.e., B-CF2 treatment) with immobilized bacteria under saline conditions, which provides an alternative technology for the rapid removal of nitrogen from saline wastewater.

The Sürgü Stream, located in the Euphrates River basin of Turkey, is used for drinking water source, agricultural irrigation and rainbow trout production. Therefore, water quality of the stream is of great importance. In this study, multivariate statistical techniques (MSTs) and water quality index (WQI) were applied to assess water quality of the stream affected by multiple stressors such as untreated domestic sewage, effluents from fish farms, agricultural runoff and streambank erosion. For this, 16 water quality parameters at five sites along the stream were monitored monthly during one year. Most of parameters showed significant spatial variations, indicating the influence of anthropogenic activities. All parameters except TN (total nitrogen) showed significant seasonal differences due to high seasonality in WT (water temperature) and water flow. The spatial variations in the WQI were significant (p < 0.05) and the mean WQI values ranged from 87.6 to 95.3, indicating “good” to “excellent” water quality in the stream. Cluster analysis classified five sites into three groups, that is, clean region, low polluted region and very clean region. Stepwise temporal discriminant analysis (DA) identified that pH, WT, Cl⁻, SO₄²⁻, COD (chemical oxygen demand), TSS (total suspended solids) and Ca²⁺ are the parameters responsible for variations between seasons, and stepwise spatial DA identified that DO (dissolved oxygen), EC (electrical conductivity), NH₄–N, TN (total nitrogen) and TSS are the parameters responsible for variations between the regions. Principal component analysis/factor analysis revealed that the parameters responsible for water quality variations were mainly associated with suspended solids (both natural and anthropogenic), soluble salts (natural) and nutrients and organic matter (anthropogenic).

Many questions about the soil pollution due to mining activities have been analyzed by numerous methods which help to evaluate the dispersion of the Metallic Trace Elements (MTE) in the soil and stream sediments of the abandoned mine of Kettara (Morocco). The transport of these MTE could have an important role in the degradation of groundwater and the health of people who are living in the vicinity. The present paper aims to evaluate the groundwater samples from 15 hydrogeological wells. This evaluation concerns the hydrogeological parameters, pH, Electrical conductivity, temperature and the groundwater level, and the geochemical assessment of Mg, Ca, Ti, Cr, Mn, Fe, Co, Ni, Zn, Cu, As, Se, Cd, Sb, Tl and Pb. Furthermore, the Metallic Trace Elements are transported in the saturated zone via the fractures network. The groundwater flow is from the north-east to south-west. The spatial distribution of As, Fe, Zn and Mn is very heterogeneous, with high values observed in the north, upstream, of the mine site. This distribution is maybe related to: i) the existence of hydrogeological structures (dividing and drainage axes); ii) the individualization of the fractures network that affects the shaly lithostratigraphical formation; iii) the transport of the contaminants from the soil towards groundwater; and iv) interaction water/rocks. Some MTE anomalies are linked to the lithology and the fracturation system of the area. Therefore, the groundwater contamination by Arsenic is detected in the hydrogeological wells (E1 and E2). This pollution which is higher than guideline standards of Moroccan drinking water could affect the public health. The hydrogeological and geochemical investigations favor the geological origin (mafic rocks) of this contamination rather than mining activities.