A remote sensing approach for characterizing lake responses to heatwaves and monsoons: a case study from India

The timing and intensity of monsoons strongly regulate the Indian subcontinent's climate, shaping water quality and availability. In 2019, a delayed monsoon following an exceptional heatwave offered a unique case to assess lake responses to climatic extremes. We analyzed satellite-derived lake turbidity and chlorophyll-a data from 42 lakes and reservoirs across the region. Our approach combined time alignment measurement analysis, cross-correlation, and clustering to investigate the main drivers of variability. Results showed that monsoon precipitation was the main driver of turbidity dynamics. Turbidity time series were more closely aligned with precipitation and air temperature, and cross-correlation analysis indicated a consistent 1-month lag between cumulative precipitation and turbidity. Available lake water level data confirmed that large fluctuations can occur within short timescales, strongly influencing water quality. Cluster analysis of annual turbidity and chlorophyll-a patterns provided insights into lake responses to heatwaves and monsoon periods. Turbidity cluster patterns largely followed precipitation patterns, whereas chlorophyll-a clusters reflected the influence of lake morphology, phytoplankton dynamics, and interactions with turbidity changes. Overall, our findings highlight the strong dependence of lake water quality on monsoon dynamics and emphasize the potential of remote sensing for monitoring and adaptive management in a changing climate.