Water quality
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Water Quality: A Comprehensive Overview
Drinking Water Quality and Public Health
Impact on Human Health
Drinking water quality is a critical factor affecting human health, particularly in developing countries where poor water quality leads to numerous waterborne diseases1. Ensuring access to clean and safe drinking water is essential for life maintenance and is recognized as a human right2 4. The United Nations' Sustainable Development Goals (SDGs) emphasize the importance of safely managed drinking water services (SMDW), which are defined as improved sources of drinking water that are accessible, available when needed, and free from contamination4.
Surveillance and Monitoring
Effective surveillance systems, often conducted by government agencies or public health services, are crucial for maintaining drinking water quality2. These systems help identify and mitigate risks associated with water contamination, ensuring public health safety. The WHO/UNICEF Joint Monitoring Programme (JMP) focuses on key parameters such as faecal contamination, arsenic, and fluoride to monitor global drinking water quality4.
Technological Advances in Water Quality Assessment
Machine Learning for Water Quality Prediction
Traditional methods of water quality assessment are often expensive and time-consuming. Recent research has explored the use of supervised machine learning algorithms to estimate the Water Quality Index (WQI) and Water Quality Class (WQC) efficiently. Algorithms like gradient boosting and polynomial regression have shown promising results in predicting WQI with high accuracy, while multi-layer perceptron (MLP) has been effective in classifying WQC3. These advancements suggest the potential for real-time water quality detection systems that are both quick and cost-effective.
Water Quality Indices (WQI)
The WQI is a valuable tool for summarizing various water quality parameters into a single value, facilitating the operational management of water resources. However, the application of WQI can vary significantly depending on the chosen parameters and methods of calculation. Studies have highlighted the challenges and contradictions that arise when different methods are used on the same dataset5 7. The use of fuzzy logic has been proposed to address these issues, providing a more adaptable WQI for specific water uses5.
Challenges and Solutions in Water Quality Management
Contamination and Public Health Risks
Contamination of drinking water remains a significant challenge, particularly in regions with rapid urbanization and industrialization. Studies have shown that water quality often deteriorates in distribution networks, with parameters like residual chlorine, E. coli, and turbidity frequently falling outside acceptable standards6. This deterioration poses risks to public health, necessitating improved treatment processes and management strategies.
Innovative Approaches to Water Quality Testing
There is a growing demand for simpler, faster, and low-cost methods for water quality testing. Emerging technologies, such as synthetic biology approaches, hold promise for rapid testing of various water quality parameters. These methods aim to reduce reliance on laboratory testing, which can be costly and time-consuming, especially in remote areas4.
Case Studies and Regional Assessments
Global and Regional Water Quality Assessments
Large-scale assessments have been conducted in various countries to evaluate drinking water quality and identify risk factors for contamination. For instance, national surveys in Ecuador and the Democratic People’s Republic of Korea (DPRK) have highlighted the prevalence of faecal contamination and the need for targeted interventions4. In regions like Dalmatia, Croatia, the WQI has been used to monitor water quality over several years, providing valuable insights into the impact of environmental factors on water quality8.
Water Quality in Mining Regions
In water-stressed and mining regions, such as the upper Olifants River catchment in South Africa, water quality is significantly affected by land use and mining activities. Studies have shown a time-critical deterioration of water quality, emphasizing the need for effective controls and improved water purification systems to mitigate health risks10.
Conclusion
Ensuring high-quality drinking water is essential for public health and sustainable development. Advances in technology, such as machine learning and innovative testing methods, offer promising solutions for real-time and cost-effective water quality assessment. However, challenges remain, particularly in regions with rapid urbanization and industrial activities. Continued efforts in surveillance, monitoring, and targeted interventions are crucial to address these challenges and protect public health.
Sources and full results
Most relevant research papers on this topic
Drinking Water Quality and Public Health
Poor drinking water quality in developing countries contributes to waterborne diseases, and this special issue aims to improve understanding and take action to improve water quality.
Highly CitedSurveillance of Drinking Water Quality Worldwide: Scoping Review Protocol
This scoping review protocol identifies and maps worldwide surveillance actions and initiatives for drinking water quality, highlighting main findings, impacts, challenges, limitations, and research gaps related to global drinking water quality monitoring.
Systematic Review
Rigorous JournalEfficient Water Quality Prediction Using Supervised Machine Learning
Supervised machine learning algorithms, such as gradient boosting and multi-layer perceptron, can efficiently predict water quality index and classify it using four input parameters, potentially benefiting real-time monitoring systems.
Highly CitedDrinking water quality and the SDGs
The SDGs have urged countries to improve drinking water quality and address faecal contamination, with household surveys being a major source of data.
Water Quality Indices: Challenges and Application Limits in the Literature
Water Quality Index (WQI) calculation methods have evolved over time, but fuzzy logic has significantly improved the adaptability of WQI to specific water uses and challenges.
Literature ReviewHighly CitedEvaluation of water quality and potential scaling of corrosion in the water supply using water quality and stability indices: A case study of Juja water distribution network, Kenya
The Juja water distribution network, Kenya, has generally good water quality, but deteriorates in the distribution network and is corrosive throughout, requiring improved treatment and management strategies for better service.
Observational StudyA critical review on the application of the National Sanitation Foundation Water Quality Index.
Using non-original parameters in the National Sanitation Foundation Water Quality Index can alter water quality results, with some scenarios showing more favorable results than others.
Literature ReviewHighly CitedWater quality evaluation by index in Dalmatia
The water quality index (WQI) is a useful tool for evaluating water quality in Dalmatia, with low sulphate and chloride concentrations indicating high sanitary quality.
Highly CitedEvaluating the surface Water quality index fuzzy and its influence on water treatment
The RWQIF, a fuzzy logic-based approach to the RWQI, can help prioritize watershed protection actions and reduce water treatment costs while improving treated water quality.
Water quality in a mining and water-stressed region
Coal mining in South Africa is associated with adverse effects on raw water quality, posing health risks to consumers if contamination sources are not reduced or water purification systems are not improved.
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