Pulipati et al. (2026) A Framework to Develop High‐Resolution Intensity–Duration–Frequency Curves: Historical Analysis and Scaling Relationships Integrating Gauge and Gridded Rainfall Products

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Identification

• Journal: International Journal of Climatology
• Year: 2026
• Date: 2026-07-07
• Authors: Yaswanth Pulipati, Balaji Narasimhan, Chakravarthy Balaji
• DOI: 10.1002/joc.70504

Research Groups

• Indian Institute of Technology (IIT) Delhi
• [Other collaborating institutions or departments]

Short Summary

This study develops a framework for creating high-resolution intensity-duration-frequency (IDF) curves using gauge and gridded rainfall products, focusing on the Indian subcontinent. The Gumbel distribution is found to be the best model for annual maximum rainfall series.

Objective

• Develop a method to create high-resolution IDF curves with durations ranging from 1 to 72 h at various return periods.
• Investigate the scale invariance theory of rainfall using hourly data from self-recording rain gauge stations.

Study Configuration

• Spatial Scale: The study focuses on the Indian subcontinent, with spatial resolution of 10 km.
• Temporal Scale: Daily and sub-daily time scales are evaluated.

Methodology and Data

• Models used: Gumbel distribution for modelling annual maximum rainfall series, machine learning regression techniques for merging gauge and gridded products.
• Data sources: Hourly rainfall data from self-recording rain gauge stations (SRRG), daily rainfall data from non-recording rain gauge stations, four gridded rainfall products (GPM, GSMaP, PERSIANN, MSWEP).

Main Results

• The Gumbel distribution is found to be the best model for annual maximum rainfall series.
• Scaling behaviour was assessed using non-central moments (NCMs) and showed good performance in modelling rainfall extremes.
• Derived scaling exponents were spatially interpolated to develop IDF curves at 10-km resolution.

Contributions

• This study provides a novel framework for creating high-resolution IDF curves, addressing the limitations of existing methods in developing countries.
• The use of machine learning regression techniques and Gumbel distribution improves the accuracy of IDF curve estimation.

Funding

• [List projects, programs, and reference codes that funded this research]

Citation

@article{Pulipati2026Framework,
  author = {Pulipati, Yaswanth and Narasimhan, Balaji and Balaji, Chakravarthy},
  title = {A Framework to Develop High‐Resolution Intensity–Duration–Frequency Curves: Historical Analysis and Scaling Relationships Integrating Gauge and Gridded Rainfall Products},
  journal = {International Journal of Climatology},
  year = {2026},
  doi = {10.1002/joc.70504},
  url = {https://doi.org/10.1002/joc.70504}
}