Spring Water Quality and Human Health: An Assessment of Natural Springs of Margalla Hills Islamabad Zone-III

Groundwater quality evaluation of the weathering mantle in crystalline basement aquifer system, southern Brazil

Groundwater is the main source of water for more than 2 billion people worldwide. In southern Brazil, the Crystalline Basement Aquifer System is composed of strategic groundwater reservoirs. Groundwater is mostly taken from shallow wells, and it is often used without any treatment, which poses a risk to public health. The present study aims to evaluate shallow groundwater quality and the geochemistry of shallow and deep groundwater located in the municipality of Canguçu, southern Brazil. The physicochemical and microbiological parameters of groundwater samples collected from shallow wells were monitored and analyzed using ANOVA variance analysis and water quality index (CCME WQI) approaches. Also, the results were compared with secondary data from deep wells. The monitored shallow wells had thermotolerant coliforms, Escherichia coli, pH, potassium, manganese, iron, and nitrate in disagreement with the guidelines of the World Health Organization. Moreover, variance analysis showed that the parameters temperature, dissolved oxygen, pH, chloride, and magnesium were the most influenced by seasonal variations. According to the CCME WQI, most samples had good quality (60%), 28% had fair quality, and 12% had poor quality. In addition, the field campaigns with higher precipitation rates also presented fair quality. Therefore, most of the shallow groundwater quality is affected by surface pollutants from the urban area, aggravated in rainy periods. Whereas deep groundwater is influenced by geochemistry mechanisms. The results revealed the risk of water consumption for public health and the urgent need for better maintenance of these wells and water treatment implementation.

Mapping reservoir water quality from Sentinel-2 satellite data based on a new approach of weighted averaging: Application of Bayesian maximum entropy

In regions like Oman, which are characterized by aridity, enhancing the water quality discharged from reservoirs poses considerable challenges. This predicament is notably pronounced at Wadi Dayqah Dam (WDD), where meeting the demand for ample, superior water downstream proves to be a formidable task. Thus, accurately estimating and mapping water quality indicators (WQIs) is paramount for sustainable planning of inland in the study area. Since traditional procedures to collect water quality data are time-consuming, labor-intensive, and costly, water resources management has shifted from gathering field measurement data to utilizing remote sensing (RS) data. WDD has been threatened by various driving forces in recent years, such as contamination from different sources, sedimentation, nutrient runoff, salinity intrusion, temperature fluctuations, and microbial contamination. Therefore, this study aimed to retrieve and map WQIs, namely dissolved oxygen (DO) and chlorophyll-a (Chl-a) of the Wadi Dayqah Dam (WDD) reservoir from Sentinel-2 (S2) satellite data using a new procedure of weighted averaging, namely Bayesian Maximum Entropy-based Fusion (BMEF). To do so, the outputs of four Machine Learning (ML) algorithms, namely Multilayer Regression (MLR), Random Forest Regression (RFR), Support Vector Regression (SVRs), and XGBoost, were combined using this approach together, considering uncertainty. Water samples from 254 systematic plots were obtained for temperature (T), electrical conductivity (EC), chlorophyll-a (Chl-a), pH, oxidation-reduction potential (ORP), and dissolved oxygen (DO) in WDD. The findings indicated that, throughout both the training and testing phases, the BMEF model outperformed individual machine learning models. Considering Chl-a, as WQI, and R-squared, as evaluation indices, BMEF outperformed MLR, SVR, RFR, and XGBoost by 6%, 9%, 2%, and 7%, respectively. Furthermore, the results were significantly enhanced when the best combination of various spectral bands was considered to estimate specific WQIs instead of using all S2 bands as input variables of the ML algorithms.

Drinking water quality monitoring, assessment and management in Pakistan: A review

In this review, the importance of a robust frame work for drinking water quality monitoring, assessment and management has been discussed. This review presents the global overview of the drinking water quality, illuminating the global challenges of water supply system from catchment to consumers and briefly discussing appropriate regulatory frameworks and risk analysis tools. It also presents meticulous summaries of water reports released by the government and non-governmental organizations with special emphasis on health-based targets, proposed strategies related to preventive risk management (through water safety planning), environmental impact assessment (EIA), and independent surveillance in Pakistan. This paper reviews various studies published in national and international journals and reports, released by the government and non-governmental organizations, to provide a summary of the current knowledge with regards to the contemporary water quality management system that is still developing in the country. Role of agencies and their policies for water quality management and monitoring is one of the most important impact categories that has been covered in this review. The reviewed publications provide strong support for claims that impacts of unsafe water on health and economy of a country are very dangerous. Improved access to safe drinking water by a development-oriented strategy can have tangible improvements in socioeconomic status of a country.

A Comprehensive Index for Measuring Water Security in an Urbanizing World: The Case of Pakistan’s Capital

Growing population, increasing urbanization, and rural to urban migration, coupled with the ongoing climate change, threaten the sustainability of cities, particularly in developing countries. Previous studies indicate numerous deficiencies in the water supply and sewage systems of Islamabad; however, a comprehensive insight into the water security assessment has not been carried out. Therefore, this study is aimed at assessing the urban water security of Islamabad by taking both human and environmental aspects into consideration. In principle, we achieve this objective by implementing the Water Security Assessment Framework, using five distinct parameters to calculate an urban water security index. The water supply dimension incorporates availability, accessibility, affordability, and the quality of drinking water in the city, whereas, sanitation and health dimension measures access to improved drainage systems as well as the state of overall hygiene of the city inhabitants. Furthermore, the water economy dimension includes water productivity and investment aspects in the study area, while the environment and ecosystem dimension looks into the current state of natural water bodies. Similarly, overall management and public support for freshwater resources are measured in the society and governance dimension. In general, we attempt to better comprehend water-security nexus in the federal capital considering it as a prerequisite to ensure a sustainable future for the city dwellers.