WATER AND WASTEWATER
Year:2024 | Volume:34 | Issue:6|Papers Count:6

The simultaneous use of the solar panel system on water tanks and canals is a novel and efficient process in today's hydrology due to its many benefits. The positive and effective effects of this method, especially in hot and dry areas around the world, have increased. Minab region in Hormozgan province has become the southern agricultural pole of Iran, due to the presence of the Esteghlal Dam basin, and with off-season crops in this region, it has met many of the country's needs in agricultural products. In the past few years, due to the decrease in rainfall and successive droughts, the supply of sustainable water for the gardens of this city has become one of the most important challenges. Based on this, to reduce the effect of solar radiation on the water passing through the irrigation canal of Minab city, the simulation of the installation of solar panels on this 8 km long canal has been done by PVSol 2021 software, and the simulation results conducted by the research team show, with a coverage factor of about 60% of the length of the canal by these panels, about 5 MW of electricity can be obtained from this renewable source. The significant point in this simulation is the 0.78 performance ratio of this power plant, which shows suitable output compared to similar cases. In addition, based on the calculations, the installation of panels with the effect of shading prevents the wastage and evaporation of more than 6000 cubic meters of water in the canal.

Non-revenue water poses a significant challenge to sustainable water management in municipalities worldwide. This study investigates the factors contributing to NRW and assesses the effectiveness of existing management strategies in three municipalities in Mpumalanga, South Africa. Through a survey-based approach, perceptions of municipality workers were collected to gain insights into the drivers of NRW and the efficiency of currently employed NRW management strategies. The findings highlight real losses; broken pipes, pipe bursts, water leakages, and storage overflows are perceived as the most significant contributing factors of NRW across all three municipalities. These results align with previous studies, emphasizing the importance of addressing real losses to mitigate NRW. Additionally, the study reveals management factors and political interference as perceived contributors to increased NRW in the municipalities. In terms of management strategies, modern flow metering is employed in two of the municipalities to control active leakage, while the third municipality relies on active leakage control equipment. Pressure management practices, automatic pressure-reducing valves, and regular asset performance assessments were identified as common practices for managing and mitigating NRW, whereas the use of smart metering technologies, modern leakage detection techniques, zoning (district metered areas), and improved estimation techniques were proposed as mitigation strategies with the potential to further reduce NRW in the three municipalities. The study fills a research gap by providing insights into the specific factors contributing to NRW in the selected municipalities and evaluating the effectiveness of existing strategies. The results of the study can inform decision-makers and water utility managers in developing targeted interventions to reduce NRW and improve water management practices. It is further recommended that future studies explore the implementation and long-term effectiveness of some of the proposed mitigation strategies to effectively address NRW in order to ensure sustainable water supply, efficient resource utilization, and improved service delivery.

The most sustainable and cost-effective approach to enhance river water quality is by actively managing its self-purification. This study's aim is to explore potential management scenarios for enhancing the river's self-purification capacity. The QUAL2Kw model was used to simulate the water quality and self-purification capacity in Dez River in Iran. The model was calibrated and validated using recorded data of three monitoring stations along the river. Five parameters, namely DO, BOD, COD, NO3-N, and NH4-N were calculated and compared with field data. The Margin of Safety was presented and added to the value of each parameter for better water management and protection. Sensitivity analysis was conducted to identify the most influential parameters in water quality simulation for Dez River. The study presented and compared the self-purification capacity across six proposed scenarios for managing water quality. The results showed that the oxidation rate, nitrification rate, and denitrification rate were the most influential parameters in simulating water quality using QUAL2Kw. Among the scenarios considered, the fourth scenario, which included urban and industrial sewage point sources as diffuse sources, exhibited the highest level of self-purification, estimated at 2,246,170.01 kg/day. In all scenarios, the self-purification capacity for COD exceeded that of other parameters along the river, with the highest COD self-purification reaching approximately 167,034.9 kg/day.

Lifelines are the determining components of survival in today's modern world and if the service of these infrastructures is threatened or destroyed due to natural disasters (especially earthquakes) and military threats, the activities of the society are disrupted and the severe failure of these systems will prolong the reconstruction period. One of the most important vital infrastructures that has a direct relationship with people's lives is the need for a water network. A review of the past earthquakes of the world and Iran shows that the components of the drinking and non-drinking water supply system have historically been considerably poor. The main goal of this paper is to prepare a model to analyze the seismic vulnerability of the water network by considering its dependence on other networks. To determine the vulnerability analysis of the water network by considering dependencies, two models were used, graph theory and Leontief. Then, after drawing the network architecture, the proximity and uncertainty matrix of all features were extracted. By multiplying the transpose of the uncertainty matrix in the independent damage analysis of each feature, the dependent damage was determined. The analysis showed the significant impact of dependence on the damage estimate of water network infrastructure; in some elements, the damage increased up to 45 times compared to the independent state. The risk of water reservoirs, water pumping stations, and water wells increased by 92%, 87%, and 62%, respectively, from the independent situation compared to the dependence in the studied area. In the case of robustness of the water network compared to the current situation, the vulnerability of water tanks, water pumping stations, and water wells will be reduced by 25%, 22% and 32%, respectively.

A reliable simulation of wastewater effluent parameters is important for reducing the operational costs of a wastewater treatment plant. In this study, optimized artificial neural networks and inclusive multiple models are used to predict the effluent biochemical oxygen demand, chemical oxygen demand and total suspended solids of a WWTPs in Shahrekord basin, Iran. The influent quality parameters (CODinf, BODinf, TSSinf and PHinf) are used as inputs to the models. The naked mole-rat algorithm is used to tune ANN parameters. This investigation compares the capabilities of ANN-NMRA with those of ANN-firefly, ANN-sine cosine algorithm, ANN-genetic algorithm and ANN models. The output of hybrid and standalone models is incorporated into an ANN model as an IMM model. Several individual models are used in an IMM model for predicting outputs. Hence, an IMM model increases the accuracy of individual models. In this study, ANN models are modified by using a goodness factor to reduce computational time. This paper presents a new preprocessing method for selecting the best input combination and analyzes the uncertainty of model and input parameters. IMM, ANN-NMRA, ANN-SCA, ANN-FFA, ANN-GA and ANN models achieve MAEs of 0.789, 0.998, 1.19, 1.26, 1.34 and 1.40 mg/L for predicting BODeff in the testing stage, respectively. The IMM model has the highest accuracy for predicting CODeff and TSSeff. A good factor reduces the computational time of ANN models by removing redundant hidden neurons. The uncertainty analysis results show that model parameters provide higher uncertainty than input parameters.

South Africa's water resources have experienced significant negative effects resulting from poor quality effluent, posing a substantial threat to public health. The main aim of this study was to evaluate the existing technological condition of wastewater treatment and sanitary infrastructure in South Africa. The rationale for conducting this study was derived from the occurrence of a recent cholera outbreak. The research employed meta-analytical techniques to review information from sources such as published journals and reports from databases such as PubMed, Science Direct, Springer and Google Scholar to investigate the impact of technological advancements in wastewater treatment and the condition of the state sanitary infrastructure in South Africa. The data was organized, summarized, and presented using basic descriptive statistics in Microsoft Excel 2019. The findings of the study reveal that ponds and lagoons have emerged as the predominant wastewater treatment technology in South Africa, with Activated Sludge technology being the second most commonly employed method. The current infrastructure is insufficient to manage the escalating volume of wastewater and the heightened water quality standards that arise from population growth and expanding industrial operations. Moreover, our study indicates that despite substantial financial allocation made by the government for the enhancement and restoration of infrastructure, the effective management of wastewater remains a persistent issue. South Africa should explore and allocate resources for emerging technologies for wastewater treatment such as membrane technology and membrane bioreactor technology, which offer advantages such as treatment of high biomass concentrations, and smaller space requirement compared to traditional systems. Other benefits of these emerging treatments include lower hydraulic retention time, high effluent quality lower biosolids and higher volumetric loading. These advantages are more applicable in South Africa, since they require a smaller amount of area compared to other conventional treatment technologies, as rapid populating growth, coupled with urbanization, has led to a shortage of available land suitable for the construction of new wastewater treatment systems to accommodate development.