Pollution

Increasing accessibility to satellite-based water quality estimates so researchers can create better models and facilitate new data-driven approaches to monitoring and understanding critical water resources.

The Coastal Resources Division administers beach water quality monitoring, public notification and data reporting to the Environmental Protection Agency and other water quality agencies.

The Caribbean Environment Programme and Cartagena Convention Secretariat webpage

Across the state, Environment Protection Authority Victoria’s (EPA) authorised officers and environmental scientists collect water samples to detect pollution and monitor the health of Victoria’s waterways.

This course aims to empower participants with a comprehensive understanding of water quality, with a focus on its importance in the Caribbean region.

This study shows that river water quality feeding a seasonally hypoxic tropical bay in Panama varies sharply with catchment land use and land cover, with pristine peat swamps producing naturally low-oxygen blackwater and more urbanized or deforested catchments showing elevated nutrients, highlighting how even moderate land-use changes can alter coastal ecosystem inputs.

This review analyzes two decades of water-quality research using multivariate statistical analysis, showing rapid growth—especially in developing countries—and identifying PCA, HCA, FA, and DA as the most widely applied techniques across studies of rivers, groundwater, and lakes.

NCEI provides access to an extensive archive of environmental data through several platforms. We deliver the climate, coastal, oceanographic, and geophysical data you need in a variety of formats.

Lake Victoria, Africa’s largest freshwater lake, is undergoing severe ecological decline driven by pollution and eutrophication that threaten its unique biodiversity and the well-being of surrounding communities, even though improved operation of existing treatment facilities could significantly reduce organic pollution on the Kenyan side.

A review of emerging methods showing how real-time monitoring, remote sensing, and advanced machine learning models are transforming the accuracy and efficiency of inland river water-quality forecasting and management, especially LSTMs, GRUs, and hybrid approaches.

A map view showing geospatial context to provide an easy and shareable snapshot of environmental/spatial data for reporting or display.

This text began as a collection of class notes for a course on applied statistical methods for hydrologists taught at the U.S. Geological Survey (USGS) National Training Center. Course material was formalized and organized into a textbook, first published in 1992 by Elsevier as part of their Studies in Environmental Science series. In 2002, the work was made available online as a USGS report.

This review highlights the limitations of widely used OLS methods in water-quality research and provides practical guidance on modern statistical approaches, such as GLS, mixed-effects models, and Bayesian analyses, that better handle the temporal, spatial, and unbalanced nature of environmental datasets.

This systematic review synthesises decades of research on surface water quality profiling, outlining major pollution sources, widely used Water Quality and Pollution Index models, key parameters, and emerging needs for more technology-driven approaches to improve monitoring and assessment.

The Global Freshwater Quality Database GEMStat provides scientifically-sound data and information on the state and trend of global inland water quality. As operational part of the GEMS/Water Programme of the United Nations Environment Programme (UNEP), GEMStat is hosted by the GEMS/Water Data Centre (GWDC) within the International Centre for Water Resources and Global Change (ICWRGC) in Koblenz, Germany.