Maurya et al. (2026) Markov chain–based characterization of rain spell persistence and transition dynamics across the Indian Ganga Basin

Identification

• Journal: Atmospheric Research
• Year: 2026
• Date: 2026-04-07
• Authors: Amit Kumar Maurya, Somil Swarnkar
• DOI: 10.1016/j.atmosres.2026.109004

Research Groups

• Department of Earth and Environmental Sciences, IISER Bhopal

Short Summary

This study assessed century-long rain spell dynamics in the Indian Ganga Basin using a multivariate probabilistic framework and Markov chain analysis, revealing a significant shift from historically coherent, long-duration rainfall to increasingly frequent, intense, and spatially fragmented short-duration events since the 1990s.

Objective

• To comprehensively assess the persistence and transition dynamics of rain spells (distinguishing short-duration (1–3 days) and long-duration (>3 days)) in the Indian Ganga Basin over a century using a multivariate and probabilistic framework, addressing the gap in integrated long-term monsoon record analysis.

Study Configuration

• Spatial Scale: Indian Ganga Basin (IGB)
• Temporal Scale: 1901–2023 (123 years)

Methodology and Data

• Models used: First-order Markov chain analysis; Joint probability-based severity index developed.
• Data sources: Century-long monsoon rainfall records (implied observational/reanalysis data).

Main Results

• A clear basin-scale shift has occurred from historically coherent, long-duration rainfall regimes to increasingly frequent, intense, and spatially fragmented short-duration events.
• Short-duration rain spells show rising persistence and recurrence across the IGB since the 1990s.
• Long-duration wet spells exhibit declining spatial continuity and stability.
• The rainfall regime is transitioning toward a convectively dominated and non-stationary state, with the entire IGB experiencing more short, high-intensity events.
• These changes amplify hydrological hazards such as flash floods, surface runoff, soil erosion, and landslides, while simultaneously limiting groundwater recharge and sustained soil moisture recovery.

Contributions

• The study introduces a novel approach by combining multivariate rain spell characteristics (duration, intensity, volume) with probabilistic modeling to capture the persistence and evolution of rainfall regimes.
• It provides new evidence of hydroclimatic reorganization across the Indian Ganga Basin.
• It establishes a probabilistic foundation for regional water management and climate adaptation strategies.
• It addresses a critical gap in integrated assessment of rain spell persistence and transition behavior using a multivariate probabilistic framework across long-term monsoon records.

Funding

• Not specified in the provided text.

Citation

@article{Maurya2026Markov,
  author = {Maurya, Amit Kumar and Swarnkar, Somil},
  title = {Markov chain–based characterization of rain spell persistence and transition dynamics across the Indian Ganga Basin},
  journal = {Atmospheric Research},
  year = {2026},
  doi = {10.1016/j.atmosres.2026.109004},
  url = {https://doi.org/10.1016/j.atmosres.2026.109004}
}