A new tool helps target conservation and pollution control on the Ganges River

A new tool helps target conservation and pollution control on the Ganges River Gaby Clark Scientific Editor Andrew Zinin Chief Editor An estimated 6 billion liters (1.6 billion gallons) of untreated sewage is discharged daily into the Ganges River Basin, home to 650 million people. Combined with seasonal monsoon flooding, the sewage and other pollutants, including agricultural runoff and industrial waste, create a major threat to public health. In a new Yale-led study, researchers developed an analytical model to identify areas along a 1,330-kilometer-long (826 miles) and 20-kilometer-wide (12 miles) corridor of the river basin that are most vulnerable to pollution. They found that urban areas on the river have the highest vulnerability. The model, a novel method for visualizing pollution vulnerability, can help policymakers and landscape designers prioritize conservation and pollution-control efforts and target interventions, such as infrastructure upgrades or conservation zoning, to sites on the river where they will have the greatest effect, the researchers said. "Good data is vital to protecting and rejuvenating the Ganges River Basin," said Anthony Acciavatti, the Diana Balmori Associate Professor at the Yale School of Architecture and the study's lead author. "It's not enough to identify the sources of pollution; we need data on where to target interventions and on what kinds of interventions are needed. Our model can guide these kinds of decisions." Ganga Rejuvenation: A Ganges field lab project The study was published in the journal PLOS Water. Acciavatti and his co-authors are members of the Ganges Lab of Collaborative Earth, a nonprofit organization that brings together scientists, engineers and other experts to develop practical solutions to environmental problems that improve the well-being of local communities. The study area for the new research spans Uttar Pradesh, India's most populous state and a patchwork of urban and agricultural landscapes that is home to 235 million people. The analysis covered 10 kilometers (6.2 miles) on either side of the Ganges River and encompassed about 26,600 square kilometers. For the study, the researchers used the Analytic Hierarchy Process (AHP), a multicriteria method that weighs multiple factors according to their relative importance. This process, when coupled with remote sensing and geospatial data, supports the analysis of large environmental systems, according to the researchers. In this case, the model was used to assess six factors that affect vulnerability to pollution: the region's population density; land use and land cover; average rainfall; drainage density; topographic slope; and average temperature. The AHP model classified about 84% of the study area as having low vulnerability, while 3.5% of the corridor, concentrated around urban areas, was determined to be highly vulnerable. The most vulnerable locations were cities located on the banks of the river, such as Varanasi, Prayagraj and Kanpur. By contrast, the model found that forested and agricultural landscapes with relatively low population densities were less vulnerable to pollution. But population density alone does not explain vulnerability to pollution, the researchers said. Among other factors that influence vulnerability is the region's drainage density, or the combination of streams and rivers that move across a landscape, they said. While the new findings can help policymakers prioritize high-vulnerability areas for pollution mitigation, infrastructure improvements and environmental monitoring, they also identify low-vulnerability areas that would benefit from conservation programs and sustainable development, the researchers noted. To account for potential limitations of the AHP approach, the researchers tested four other analytical methods to compare outcomes and construct a composite analysis. The composite identified stretches of the river that, according to all models, are particularly vulnerable to pollution. For example, areas with cities had higher levels of vulnerability across the models. But the composite also showed that forest and cropland areas with low population densities were more vulnerable to pollution as rainfall increased, which indicates a need to adopt holistic approaches to mapping vulnerability to pollution along the river, the researchers said. "Data concerning water quality and industrial and agricultural impact is scarce for this region," said Acciavatti, who directs the Ganges Lab. "Our model is meant to provide a foundation for assessing risk that can be built upon. It's a first step toward the goal of protecting and reviving a river system that is one of the world's most polluted waterways." Publication details Anthony Acciavatti et al., Sustainable river management using Analytical Hierarchical Process on remote sensing data: Estimating riverscape vulnerability for Ganga, the world's most densely populated river basin, PLOS Water (2026). DOI: 10.1371/journal.pwat.0000394 Journal information: PLOS Water Provided by Yale University