Study on Backwater Effect Due to Polavaram Dam Project under Different Return Periods

In this study, we present a scenario to evaluate the backwater impacts on upstream of the Polavaram dam during floods. For this purpose, annual peak discharges across the different gauge stations in river stretch considered for flood frequency analysis. Statistical analysis is carried out for discharge data to estimate probable flood discharge values for 1000 and 10,000 years return period along with 0.1 and 0.14 million m3/s discharge. Furthermore, the resulting flood discharge values are converted to water level forecasts using a steady and unsteady flow hydraulic model, such as HEC-RAS. The water surface elevation at Bhadrachalam river stations with and without dam was estimated for 1000 and 10,000 years discharge. Unsteady 2D flow simulations with and without the dam with full closure and partial closure modes of gate operation were analysed. The results showed that with half of the gates as open and all gates closed, water surface elevation of 62.34 m and 72.34 m was obtained at Bhadrachalam for 1000 and 10,000 years. The 2D unsteady flow simulations revealed that at improper gate operations, even with a flow of 0.1 million m3/s, water levels at Bhadrachalam town will be high enough to submerge built-up areas and nearby villages

Mapping the scarcity of data on antibiotics in natural and engineered water environments across India

Antimicrobial resistance is a growing public health concern, increasingly recognized as a silent pandemic across the globe. Therefore, it is important to monitor all factors that could contribute to the emergence, maintenance and spread of antimicrobial resistance. Environmental antibiotic pollution is thought to be one of the contributing factors. India is one of the world’s largest consumers and producers of antibiotics. Hence, antibiotics have been detected in different environments across India, sometimes at very high concentrations due to their extensive use in humans and agriculture or due to manufacturing. We summarize the current state of knowledge on the occurrence and transport pathways of antibiotics in Indian water environments, including sewage or wastewater and treatment plants, surface waters such as rivers, lakes, and reservoirs as well as groundwater and drinking water. The factors influencing the distribution of antibiotics in the water environment, such as rainfall, population density and variations in sewage treatment are discussed, followed by existing regulations and policies aimed at the mitigation of environmental antimicrobial resistance in India, which will have global benefits. Then, we recommend directions for future research, development of standardized methods for monitoring antibiotics in water, ecological risk assessment, and exploration of strategies to prevent antibiotics from entering the environment. Finally, we provide an evaluation of how scarce the data is, and how a systematic understanding of the occurrence and concentrations of antibiotics in the water environment in India could be achieved. Overall, we highlight the urgent need for sustainable solutions to monitor and mitigate the impact of antibiotics on environmental, animal, and public health

Pharmaceutical pollution of the world's rivers

Environmental exposure to active pharmaceutical ingredients (APIs) can have negative effects on the health of ecosystems and humans. While numerous studies have monitored APIs in rivers, these employ different analytical methods, measure different APIs, and have ignored many of the countries of the world. This makes it difficult to quantify the scale of the problem from a global perspective. Furthermore, comparison of the existing data, generated for different studies/regions/continents, is challenging due to the vast differences between the analytical methodologies employed. Here, we present a global-scale study of API pollution in 258 of the world's rivers, representing the environmental influence of 471.4 million people across 137 geographic regions. Samples were obtained from 1,052 locations in 104 countries (representing all continents and 36 countries not previously studied for API contamination) and analyzed for 61 APIs. Highest cumulative API concentrations were observed in sub-Saharan Africa, south Asia, and South America. The most contaminated sites were in low- to middle-income countries and were associated with areas with poor wastewater and waste management infrastructure and pharmaceutical manufacturing. The most frequently detected APIs were carbamazepine, metformin, and caffeine (a compound also arising from lifestyle use), which were detected at over half of the sites monitored. Concentrations of at least one API at 25.7% of the sampling sites were greater than concentrations considered safe for aquatic organisms, or which are of concern in terms of selection for antimicrobial resistance. Therefore, pharmaceutical pollution poses a global threat to environmental and human health, as well as to delivery of the United Nations Sustainable Development Goals

Screening and Absolute Quantification of a β-lactamase Resistance Gene NDM-1 in Lake Sediment

New Delhi Metallo-β-lactamase-1(NDM-1) is an enzyme that hydrolyzes a wide range of β-lactams antibiotics, including carbapenems. The presence of the NDM-1 inhibits the potential of β-lactam antibiotics in treating infections caused by bacterial strains carrying such resistances, thus leaving minimal treatment options available. Due to this, the rapid distribution of NDM-1 harboring bacteria accounts for a significant public health menace worldwide. These bacteria have been detected in clinical specimens and environmental compartments where bacterial infections are ubiquitous. In this study, identification and absolute quantification of NDM-1 in sixteen lake sediment samples collected in and around Hyderabad, India, was carried out using a real-time quantitative polymerase chain reaction (qPCR), and results were expressed in gene copy number/ng (nanogram) of template DNA. Thirteen samples (out of sixteen) displayed a positive signal for NDM-1 during the qPCR analysis with the highest gene copy number/ng of template DNA (71.8) being observed in the Amberpet STP. Three samples, samples those from Durgamcheru lake, Kandi lake, and Singur dam, were negative for the NDM-1 during the qPCR analysis. Hierarchical clustering analysis was performed to categorize the sampling location into different clusters based on pollution sources and the observed results were expressed in the form of a dendrogram. © 2022 University of Tehran. All rights reserved

Modeling transport of antibiotic resistant bacteria in aquatic environment using stochastic differential equations

Contaminated sites are recognized as the “hotspot” for the development and spread of antibiotic resistance in environmental bacteria. It is very challenging to understand mechanism of development of antibiotic resistance in polluted environment in the presence of different anthropogenic pollutants. Uncertainties in the environmental processes adds complexity to the development of resistance. This study attempts to develop mathematical model by using stochastic partial differential equations for the transport of fluoroquinolone and its resistant bacteria in riverine environment. Poisson’s process is assumed for the diffusion approximation in the stochastic partial differential equations (SPDE). Sensitive analysis is performed to evaluate the parameters and variables for their influence over the model outcome. Based on their sensitivity, the model parameters and variables are chosen and classified into environmental, demographic, and anthropogenic categories to investigate the sources of stochasticity. Stochastic partial differential equations are formulated for the state variables in the model. This SPDE model is then applied to the 100 km stretch of river Musi (South India) and simulations are carried out to assess the impact of stochasticity in model variables on the resistant bacteria population in sediments. By employing the stochasticity in model variables and parameters we came to know that environmental and anthropogenic variations are not able to affect the resistance dynamics at all. Demographic variations are able to affect the distribution of resistant bacteria population uniformly with standard deviation between 0.087 and 0.084, however, is not significant to have any biological relevance to it. The outcome of the present study is helpful in simplifying the model for practical applications. This study is an ongoing effort to improve the model for the transport of antibiotics and transport of antibiotic resistant bacteria in polluted river. There is a wide gap between the knowledge of stochastic resistant bacterial growth dynamics and the knowledge of transport of antibiotic resistance in polluted aquatic environment, this study is one step towards filling up that gap

Analysis of spatio-temporal variation of hydroclimatic variables of the Krishna river basin under future scenarios

Climate change and intensified human activities are expected to alter the natural hydrological cycle would cause changes in the distribution of water resources and their availability across space and time. Therefore, the present study focused on understanding the spatiotemporal variations of hydroclimatic variables namely rainfall, surface runoff, water yield, and the Aridity Index (AI) of the Krishna River Basin (KRB) under combined impact of climate and Land Use/Land Cover (LULC) change scenarios. From trend analysis, the best model (CNRM-CM5 driven RCM) projected an increasing trend in rainfall under both RCP 4.5 and 8.5 scenarios for the entire century. Results indicated that, except for the central part, most of KRB experiences high runoff and water yield conditions under both RCP 4.5 and 8.5 scenarios in the mid and end centuries, conversely it may face low runoff and water yield conditions in the early century. Most of the central part is in arid and semi-arid conditions and, the eastern part of the basin is in dry sub-humid conditions, while the Western Ghats, Palleru, and Munneru regions of the basin fall under humid and hyper humid regions under RCP 4.5 scenario. Whereas the majority of the basin falls under humid and hyper humid regions under RCP 8.5 scenario except for the central and few other parts of the basin. In light of this, it was essential to review the current water management strategies and plan future projects to provide efficient and effective ways to mitigate the adverse impacts resulting from climate variability. © 2022 International Association for Hydro-Environment Engineering and Research

Modeling Fluoroquinolone Resistance in Polluted Aquatic Environment of a River

Excess use of antibiotics has led to antibiotic pollution in the environment, and now polluted sites have become hotspots for evolution and spread of antibiotic resistance in environmental bacteria. Subinhibitory concentration of antibiotics combined with other pollutant exerts selective pressure on environmental microbes, driving evolution and spreading antibiotic resistance. A mathematical model has been developed to have a better understanding of the subject of development of antibiotic resistance and its management in the aquatic environment. The model includes state variables such as fluoroquinolone, organic matter, heavy metals, resistant bacteria, and susceptible bacteria. The model was applied to the Musi River, which is heavily polluted with antibiotics. Simulations were carried out with hydraulic conditions and initial boundary conditions for state variables using actual site-specific data. Spatial pattern predicted by simulated results of the model is able to match with the observed spatial pattern of proliferation of resistance in the river. The developed model is also simulated for different pollution loading scenarios to predict and compare the future conditions for the river management. The simulated results showed that factors such as substrate concentration, antibiotic concentration, horizontal rate of transfer of plasmid, total population density of bacteria, and rate of losing plasmid dictate the dynamics of resistance in the river

Evaluation of sustainability of river Krishna under present and future climate scenarios

The rise in greenhouse gases, carbon dioxide concentrations in the atmosphere, along with the warmer climate and Land Use/Land Cover (LULC) changes may have a significant impact on water resources of the local hydrological regime. Hence, it is essential to assess the river basin response to corresponding changes to providing a reliable, resilient, sustainable management system in future. So, the present study focuses on providing a robust framework to evaluate sustainability of river Krishna under future climate scenarios. A novel framework was developed with the help of Bayesian Networks (BNs) known as the River Sustainability Bayesian Network (RSBN) model. It contains twenty-one parameters, which covers socio-economic and environmental dimensions of sustainability. In these twenty-one parameters, ten parameters are root (independent) nodes, and the other eleven parameters were child nodes of these root nodes. The proposed RSBN model offers a unique combination of parameters, which includes various aspects of river basin such as water quality, quantity, climatic conditions, and LULC changes along with ecological management in the basin. The parameters used are flexible enough to modify based on user requirements. Under the Representative Concentration Pathway (RCP) 8.5 scenario, the model shows basin progress towards medium sustainability from mid-century onwards, whereas there is no significant change in river sustainability under the RCP 4.5 scenario. The sustainability of the basin is expected to be highly sensitive to extreme events followed by changes to water stress, environmental flow. The present model framework may help policymakers and water managers for sustainable planning and management of water resources of the basin

Risk-Assessment Method to Forecast Health Hazards Correlated with Distribution of NDM-1 Gene in Waterbodies Surrounding Hyderabad, India

The development of pathogenic bacteria encompassing antibiotics-resistant genes (ARGs) is a severe environmental concern related to human health. Among all antibiotics administered to humans, the β-lactam group's antibiotics account for two-thirds of the total weight due to its clinical effectiveness and low toxicity. This study investigated the abundance of gene NDM-1 (New Delhi metallo-β-lactamase-1) as an emerging contaminant in Hyderabad, India's water bodies using a quantitative polymerase chain reaction (qPCR). The quantitative microbial risk assessment (QMRA) method was applied to forecast the human health risk linked to ingestion/subjection of surface water with bacteria containing the NDM-1 gene. The gene copy number of the NDM-1 in the exposure route was taken into consideration for the determination of risk in best- and worst-case scenarios. The lowest and highest gene copy numbers were selected as the best-case scenario and the worst-case scenario, respectively. The outlet of Amberpet sewage treatment plant (STP) exhibited the lowest risk, 2×10-2, i.e., 2 of 100 people are exposed to infection. In contrast, Mir Alam tank lake exhibited the highest risk, 77×10-2, i.e., 77 of 100 people are exposed to infection. Risk assessment categorized the sampling locations into low, medium, and high risk of infection. Sampling areas with a low risk of infection included Amberpet STP outlet (2×10-2), Ameenpur lake (24×10-3), Manjeera water treatment plant (WTP) outlet (26×10-3), and Osman Sagar lake (24×10-3). Sampling locations with a medium risk of infection included Alwal lake (23×10-2), Durgamcheru lake (47×10-2), Hussain Sagar lake (21×10-2), Mominpet lake (27×10-2), and Saroor Sagar lake (43×10-2). Sampling zones including Fox Sagar lake (53×10-2), Himayat Sagar lake (70×10-2), Kandi lake (56×10-2), Manjeera dam (66×10-2), Mir Alam tank lake (77×10-2), Nagole lake (54×10-2), Safilguda lake (55×10-2), and Singur dam (57×10-2) were categorized as zones with a high risk of infection. The findings of the occurrence of the NDM-1 gene containing bacteria in water bodies surrounding Hyderabad and its related risk will be valuable for developing strategies to safeguard the public from the threat of clinical risks correlated with the dissemination of NDM-1

Enhanced electrokinetic remediation (EKR) for heavy metal‐contaminated sediments focusing on treatment of generated effluents from EKR and recovery of EDTA

Electrokinetic remediation (EKR) is one of the most successful remediation techniques to treat the sediments contaminated with heavy metals. EDTA is the most widely used enhancing agent to improve the transport process in EKR. But often the generated effluents from EKR contains a high concentration of heavy metals, which cannot be disposed of without treatment. The major objective of this study includes the estimation of optimal concentration of chelating agent EDTA, followed by treatment of contaminated sediments by EKR technique for heavy metal removal. The effluents generated from EKR were further studied for recovery and reuse of EDTA and for safe discharge of heavy metals. The optimum concentration of EDTA was found as 0.05 M with a solid-to-liquid ratio as 1:10. When fresh EDTA was used as enhancing agent the average removal of heavy metals obtained as 74.8% with EKR, whereas the application of recovered EDTA in treatment process in first, second, and third cycle showed the slight reduction of heavy metals of about 71.1%, 63.5%, and 52.1%, respectively. The heavy metal removal by recovered EDTA was effective in reduction of heavy metals up to three cycles of re-use while reducing the ecological risk in sediments. Practitioner points: Treatment of contaminated sediments with heavy metals achieved by electrokinetic remediation (EKR) technique enhanced with EDTA. The recovery of EDTA and heavy metal reduction from the generated effluents during EKR treatment were performed by the addition of FeCl3 and Na2PO4, and optimized concentration was evaluated. This study found that the use of recovered EDTA in EKR treatment has effectively reduced the risk associated with heavy metals