A source-pathway-receptor framework for quantifying ecological risk to shallow- and deep-rooted vegetation under heavy metal contamination

Heavy metal contamination in river basins poses a global challenge to vegetation health, crop productivity, and long-term ecological security. Existing vegetation ecological risk assessment methods typically assume uniform vegetation exposure and often overlook the influence of contamination sources and hydrological pathways on vegetation vulnerability. This study develops a vegetation ecological risk assessment framework using a source-pathway-receptor approach to quantify spatiotemporal risk patterns at the root level. An integrated environmental risk assessment was first conducted for the pre- and post-monsoon seasons of 2023. Subsequently, contamination source intensity, environmental pathway intensity, and vegetation receptor vulnerability were combined using the entropy weighting method to estimate vegetation ecological risk within shallow-root (S-VER) and deep-root (D-VER) systems. The derived risk patterns were validated using vegetation response obtained from a normalized difference vegetation index. Findings revealed a moderate level of S-VER influenced by surface hazards in 49% and 43% of sub-basins during the pre- and post-monsoon season. Seasonal surface hydrological processes regulated these patterns within the ecological function and agricultural production zones. Conversely, D-VER exhibited relatively stable patterns with low-to-moderate risk observed in 51% and 46% of the sub-basins due to persistent subsurface contamination and limited seasonal variability. The lower Hindon Basin exhibits elevated ecological risk due to cumulative upstream contamination loading, intensified hydrological forcing, and reduced vegetation resilience. A negative relationship between vegetation response and estimated ecological risk further supports these patterns. The study provides a scientific basis for evaluating vegetation ecological risk in contaminated river basins and underscores the need for targeted monitoring and sustainable watershed management strategies.