Journal of Applied Research in Water and Wastewater
Volume:10 Issue: 1, Winter-Spring 2023

Rivers are valuable sources of water supply for various purposes. These sources are seriously exposed to quality degradation due to the entry of various contaminants. Therefore, proper monitoring and quality management of these resources could be very important. In the present study, the quality of the Balikhlou river in Ardabil province, northwest of Iran, was investigated by surveying the trend of changes in river quality parameters, as well as water quality indices. In this study, after collecting the available data, by determining the trend of changes in quality parameters, the suitability of the studied river water quality for drinking and irrigation purposes was determined. The results indicated that there is an inverse relationship between changes in river discharge rate and the concentration of qualitative parameters. Therefore, it was found that salinity-containing pollution sources enter the river upstream of the desired station. Besides, the results of water quality indices showed that the water quality of the studied river is very poor for drinking (WQI>75). In addition, the results of water quality assessment for irrigation use based on SAR, KI, and SSP indices were generally considered inappropriate (SAR>26, KI>1, SSP>50), EC was often permissible (750<EC<2250), and MH was appropriate (MH<50). Our study highlights the importance of river water quality studies over time and thus can lead to better management of these valuable resources.

Surface water quality management is very important. Qualitative indicators of water pollution can indicate the trend of quality changes over time and place. The aim of this study was to evaluate the quality of Golin river using IRWQISC index. For this purpose, the Golin river water was sampled twice a month in a period of one year from May 2019 to April 2020 in Najar village station located in downstream of river. Different parameters which evaluated in this study were DO, pH, BOD5, COD, nitrate, phosphate, electrical conductivity, total hardness and turbidity. The results of the study using the IRWQISC index showed that the range of the index values in the warm months of the year was "between" 30.57 to 32.17 with relatively poor-quality category. While in the cold months of the year the index values obtained "between" 27.36 to 27.83 with poor quality category. In general, according to the results from the annual average of the IRWQISC index, the numerical value was obtained as equal to 29.62, which showed Golin river in poor quality category. The results which presented in this study can be useful for different organization decision to perform their water related projects on Golin river.

The issue of water resource management has become extremely complicated due to the droughts of the last two decades and the competition among the drinking sector, agricultural sector, and international Hamoun wetland to use water. To analyze the status and help managers in policy analysis and decision-making, this research adopted an integrated water resource model (WEAP) with a decision support system (DSS) approach to study the effect of drought on rural and agricultural development and its economic impacts in the region. So, the Iranian government’s water development projects were simulated within 11 scenarios for a medium-term period (up to the 2030 horizon) and the implications of their implementation for the development of the rural and agricultural sectors were assessed. According to the results, if Afghanistan observes Iran’s water rights, there will still be a great amount of unmet water demand (314.53 million m3) for the agricultural and wetland sectors. However, if this scenario is realized, the unmet demand will decrease by about 196 million m3 versus the status quo and the agricultural sector’s profit will increase by about 314 billion IRR, which will be very helpful for rural development. So, relevant officials should put their best effort into realizing the water right. It is suggested to strengthen water diplomacy between the two main stakeholders in the region in order to reduce the persistence of drought.

During the recent few decades, the use of various models has been regarded as a promising option to predict groundwater level (GWL) in any given region using a wide variety of data and relevant equations. The lack of trustworthy and comprehensive data is, nevertheless, one of the most significant obstacles that must be overcome in order to analyze and anticipate the depletion of groundwater in the context of water management. Because of this, the implementation of artificial intelligence (AI) models that are able to predict the GWL with high accuracy using a reduced amount of data is unavoidable. In this work, the GWL variations of Lur plain were simulated using GMS model by utilizing the available data and maps. The accuracy of model was assessed at both phases i.e. validation and calibration. Following that, GA-ANN and ICA-ANN approaches, together with ELM, ORELM, and GMDH models, were used in order to fulfill the demand for too smaller volumes by AI procedures. According to the results, the ORELM output had the highest correlation with the observed information, which indicates that it is the most accurate model in this regard. The correlation coefficient for this model was 0.976. Because of this, instead of utilizing a complicated GMS model that needs a significant amount of data for the simulation, an ORELM model can be used to reliably forecast the GWL in the Lur plain. This simple model allows the researchers to accurately predict changes in GWL during rainy and non-rainy years compared to other complicated and time-consuming numerical models.

This paper assesses the environmental impact of the wastewater treatment plant (WWTP) of the Cameroon Real Estate Company (CRE) camp in the "Cité-Verte" district in Yaoundé (Cameroon) and the causes of its malfunction. The study was carried out in two stages. The first stage consisted of describing the wastewater treatment steps of the WWTP, and analyzing the staff interviews in order to determine the causes of malfunction that had been suspected. The second phase consisted of collecting water samples at the entry of the WWTP (P1), inside the WWTP (P2), and at the outlet of the WWTP (P3). This, in order to produce a list of the WWTP's collecting systems, characterize the various types of wastewater (P1 and P2) and the treated wastewater (P3), and then determine the effect of effluent discharges on the environment. Finally, the structural and operational malfunctions of WWTP are identified using the Ishikawa and the Pareto diagrams. The results of water characterization show that the mean values of pH (7.7), EC (1059.3 μS/cm), TDS (524.6 mg/L), T° (23.6 °C), BOD5 (10.8 mg/LO2), NO3- (2.3 mg/L), and fecal coliforms (447.3 CFU/100 mL) are below the acceptable limit values of the Cameroonian standard of treated wastewater discharge. However, the mean values of TSS (269.3 mg/L), PO43- (1661.6 mg/L), K+ (1220.6 mg/L) and Escherichia coli (10133.3 CFU/100 mL) exceed the recommended values set by the Cameroonian standard of treated wastewater discharge. The values of the wastewater parameters at the sampling point P3 are globally lower than those at the sampling point P1 but higher than Cameroon’s standard for PO43- and K+. These results demonstrated that the current system (filters and plants) is appropriate but not optimal. The Pareto diagram reveals that the inadequate plant controls, unfavorable working conditions, lack of maintenance andsystematic control, and outdated equipment represent 20% of the causes responsible for 80% of the WWTP's malfunction. Therefore, the implementation of corrective and preventive measures is essential for better monitoring and determinization of the optimal performance of the WWTP of the CRE camp in the "Cité-Verte".

Crude oil is released into the water sources during exploration, extraction or displacement operations due to the partial dissolution, and it can remain as a layer on the surface of the water or become emulsive. Crude oil emulsion is very stable due to the presence of asphaltene and cannot be removed by the common methods. In this research, iron oxide nanoparticles were coated with oleic acid (OA), stearic acid (SA), sodium dodecyl sulfate (SDS), cetyltrimethylammonium bromide (CTAB), polyvinylpyrrolidone (PVP) and polyoxyethylene (POE), by using the same method. After synthesizing iron oxide nanoparticles and coating their surface with fatty acids and surfactants, we have tried to break the crude oil emulsion in water and remove the crude oil from the environment by adsorption via these nanoparticles. Fourier transform infrared spectroscopy (FT-IR), transmission electron microscope (TEM), scanning electron microscope (SEM), thermal gravimetric analysis (TGA), vibration sample magnetometer (VSM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffraction (XRD) and Zeta potential devices were used to identify nanoparticles and their characteristics. Demulsification of crude oil in water (O/W) with nanoparticles coated with fatty acids and surfactants was studied. UV-Vis spectrophotometery was used to determine the amount of crude oil adsorption by nanoparticles. From the results, the nanoparticles coated with the fatty acids with smaller chains could more absorb the crude oil. The highest adsorption (98.03 %) was recorded for iron oxide nanoparticles coated with polyoxyethylene (Fe3O4@POE) and the lowest percentage (46.69 %) is related to the nanoparticles coated with palmitic acid in an alkaline medium. Alkalinization of the medium while coating the nanoparticles with fatty acid has increased only the efficiency in the case of oleic acid while led to a significant decrease in the efficiency for palmitic and stearic acids compared to the neutral state.

Surface water pollution is a challenge due to effluent discharge from land-based factors like agro-based sectors, settlements, and poor sanitation. The research investigated the spatial and seasonal variation of physico-chemical and biological water quality due to land use changes along the Thika River sub-catchment, Upper Tana, Kenya. The study applied purposive sampling technique from the different zones within the catchment during the dry and wet season of 2021. The samples were tested for physico-chemical and microbial contaminants. R-studio was used to calculate the mean values and t-test performed at a 95% confidence interval to determine variation of the parameters in the two seasons and mean levels compared to the Kenya Bureau of Standards (KEBS) 2010 and the World Health Organization (WHO) acceptable quality for drinking water. There was significant variation in sulphate and nitrate concentration, total coliform and fecal coliform and no significant variations in physical parameters throughout the seasons. The total coliform and fecal coliform exceeded KEBS and WHO limits.

This research was conducted with the aim of investigating temporal and spatial changes in the quality of underground water in Marvast plain in order to be used in planning for these resources. For this reason, the underground water quality data of Marvast Plain was prepared and selected for the research through the review and test of Run Test and Makos for the statistical period of 21 years (2001 to 2021). By performing trend analysis, the presence of trend in all data was determined and during the implementation of geostatistical methods, the trend was removed. Also, for the implementation of geostatistical methods, half-variable and half-variable cross-plot were chosen and due to the higher R2, lower RSS and stronger spatial structure, the best model was selected, and the exponential model was found to be suitable for most of the parameters. Then RBF, IDW with powers of 1 and 2, normal kriging and normal cokriging were used to perform interpolation. The most accurate method was selected for each parameter with the mutual evaluation method and three error estimation indices MAE, MBE and RMSE. The results showed that the normal cokriging method is the best method for most parameters (cation, anion, Ec, Cl, Ca, K, Mg, Na and TH). For the SAR, So4 and pH parameters, the normal kriging method and for the Na percentage parameter, the radial basis function was found to be the most suitable method. The results showed that the concentration of most parameters has an upward trend from west to east and south to north. Also, with the passage of time, the trend of reducing the quality of underground water was observed.

The occurrence of global environmental crises, combined with population growth and increased global water demand, highlights the pressing need for effective management of water resources. This includes comprehensive attention to water administration, consumption, and reporting. The objective of this research is to investigate the frameworks of global water reporting and provide a robust and comprehensive model for water reporting in Iranian listed companies. To achieve this goal, a survey was conducted in 2023 involving sixteen experts in water reporting. The participants consisted of engineers and managers from prominent companies in the water consumption and sustainability reporting sector, as well as university professors specializing in sustainability studies and research. The aim was to identify the appropriate components of water reporting for companies listed on the Iran Stock Exchange. Subsequently, the Best-Worst Method (BWM), a multi-criteria decision-making approach, was employed to determine the importance of each reporting item and establish the priorities of the reporting components. The results revealed that the main components of water reporting, ranked in order of importance, are as follows: performance, business strategies, water-related impacts, metrics, water governance, risks and opportunities, and finally regulations and rights. These findings hold valuable implications for stock market policymakers and company managers. By recognizing these critical indicators and components, they can effectively mandate water reporting for Iranian listed companies. Furthermore, they can ensure that water reporting accurately reflects the significant aspects of corporate operations related to water resources.

In this study, a probabilistic method was proposed to determine the stable riprap as a scour control measure downstream of a stilling basin, using the Monte Carlo Simulation Technique. The Kan diversion dam in Iran was selected as a case study, and various uncertainties in the model, including hydraulic parameters for different design flood events, were taken into account during the analysis. Moreover, the relationship between the probability of failure, structure lifespan, and riprap sizing was also investigated. The results indicated that the estimates for riprap data followed a normal distribution. By utilizing the characteristics of this distribution, such as the mean and coefficient of variation, the stable riprap sizes were calculated based on the desired probability of failure and the structure lifespan. For instance, when considering a 5% probability of failure, the riprap size was determined to be 0.203 m for a 50-year design flood. Similarly, for larger floods, such as a 200-year design flood, the riprap size needed to be increased by 65%. Furthermore, as the structure lifespan increased from 25 years to 200 years, the riprap stone size saw an approximate 25% increase for a 200-year design flood.

In the realm of industrial development, a variety of organic pollutants, including petroleum compounds, have emerged as persistent environmental concerns due to their non-degradable nature. To effectively address this issue, plasma technology has garnered significant attention as a promising approach for wastewater treatment, offering the capability to eliminate a wide spectrum of contaminants. This research capitalizes on Response surface methodology (RSM) to explore the independent and combined effects of key factors such as initial concentration, pH, applied voltage, and time on the degradation of a specific pollutant known as PNP, utilizing non-thermal discharge plasma technology. The outcomes of this investigation unveiled several noteworthy trends. Enhancing the initial pH, applied voltage, and reaction time while reducing the initial concentration exhibited a positive influence on the removal efficiency. Additionally, the study examined the interactions among these variables, revealing both antagonistic and synergistic effects. Specifically, antagonistic relationships were observed between initial concentration and initial pH, initial concentration and applied voltage, as well as applied voltage and time. On the other hand, a synergistic effect was noted between initial concentration and time. By employing an optimization approach, the optimal conditions for achieving PNP degradation were determined to be as follows: an initial concentration of 50 mg/L, pH of 9.7, applied voltage of 13.75 kV, and a reaction time of 8 min, resulting in an impressive removal efficiency of 96.503%. The findings of this study underscore the immense potential of non-thermal discharge plasma technology and the utilization of RSM in advancing the optimization of advanced oxidation processes for effective wastewater treatment.

Industrial activities present a significant threat to the environment and natural ecosystems like water and soil due to the release of toxic metals. This article primarily concentrates on the identification and isolation of bacteria, with the goal of effectively eliminating pollutants from industrial wastewater. In order to achieve this goal, the study was conducted to assess the ability of bacterial strains to tolerate copper (Cu) and zinc (Zn), as well as their antibiotic resistance and ability to tolerate elevated metal concentrations. The resistance of the isolates to various metals and antibiotics were assessed using the minimum inhibitory concentration (MIC) values and disc diffusion (DD) method, respectively. The technique of colony PCR was employed to determine the identity of the bacteria that were separated. Resistance to multiple antibiotics was assessed, including Penicillin, Sulfamethoxazole, Tetracycline, Erythromycin, Amoxicillin, Cefoxitin, Streptomycin, Chloramphenicol, Vancomycin, Gentamycin, Cephalothin, Rifampicin, and Novobiocin. In the current investigation, a total of 5 bacteria with a positive gram stain and 7 bacteria with a negative gram stain were identified. The study found that the effluent from the wastewater treatment plant in Razi industrial town showed resilience to copper ions, especially at a concentration of 7mM. The effluent wastewater from the refinery unit exhibited the greatest level of tolerance towards zinc, with a concentration as high as 6mM. The rise in copper and zinc levels in industrial wastewater treatment plants causes microorganisms to develop resistance to these heavy metals. The study of Gram-positive resistant bacteria conducted in this research focused on the examination of their susceptibility to zinc and copper. Notably, Staphylococcus hominis displayed resistance to a majority of the antibiotics evaluated. However, Kocuria rosea demonstrated sensitivity to all antibiotics. Agrobacterium fabrum exhibited susceptibility to all antibiotics as opposed to other Gram-negative bacteria resistant to zinc and copper. The findings of this study indicated that some strains displayed a degree of resistance to both antibiotics and heavy metals. The presence of heavy metals in bacteria isolated from a wastewater treatment plant exhibited the capability to restrict antibiotic resistance.