Causes, impacts, and risk reduction of flooding from heavy metal-mixed wastewater: A case study in San Mateo Atenco, Mexico
Year: 2025
Type: article
Abstract: Climate change has increased urban floods, while heavy metal pollution has affected several rivers across different continents, exacerbating environmental issues globally. Both phenomena can potentially increase health and environmental risks in flood-prone areas, mainly in Low- and Middle-Income Countries. This technical note reports a forensic analysis applied to a case study in San Mateo Atenco, Mexico, to determine the causes and impacts of the 2018 flooding disaster. In addition, a Nature-Based Solution is proposed for achieving the Sustainable Development Goals 6.6, 11.5, 13.1, and 15.3. In the study area, the disaster transported heavy metals mixed with untreated wastewater illegally discharged from the Lerma River to the plain areas, affecting 3266 inhabitants and contaminating over 168.4 ha, resulting in economic damage (tangible) of USD 5.82 million. A mixed methodology was implemented to recreate the flooding scene, combining social and remote sensing science tools with a Digital Elevation Model in a Geographical Information System. The study found that the extreme hydrometeorological event and other factors that raised the River channel bottom caused the flooding. A vegetated Riparian Buffer Zone, designed as a detention basin and implemented at the study site, can control overflow and reduce flood risk during peak flows; this strategy can also help mitigate climate change locally, limit urban growth, and reduce pollution from upstream urban dust. • Flood extent and volume data aid in determining the river's hydraulic capacity. • A riparian buffer zone designed as a detention basin can reduce flood risk. • Social and remote sensing sciences help reconstruct wastewater flood scenes. • Semi-structured interviews help identify flood causes in forensic analysis.
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,200
OpenAlex ID: W4409724674
