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, offering a unique case to assess lake responses to climatic extremes. We analysed 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 cluster analysis 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 one-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.

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

Rossana Caroni
Primo
;
Anna Joelle Greife
Secondo
;
Mariano Bresciani;Claudia Giardino;Marina Amadori
Penultimo
;
Monica Pinardi
Ultimo
2025

Abstract

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, offering a unique case to assess lake responses to climatic extremes. We analysed 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 cluster analysis 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 one-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.
2025
Istituto per il Rilevamento Elettromagnetico dell'Ambiente - IREA - Sede Secondaria Milano
Chlorophyll-a, Heatwave, Lakes, Monsoon, Satellite data, Turbidity
File in questo prodotto:
File Dimensione Formato  
JWC-D-25-00097_REV.pdf

solo utenti autorizzati

Descrizione: Proof
Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 1.28 MB
Formato Adobe PDF
1.28 MB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/555890
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact