Log in

Utilizing advanced and modified conventional trend methods to evaluate multi-temporal variations in rainfall characteristics over India

  • Research
  • Published:
Theoretical and Applied Climatology Aims and scope Submit manuscript

Abstract

Adequate and consistent rainfall is essential for sustaining water resources, agricultural production, and overall economy of a nation. To explore the variability and changes in rainfall system, the most common and widely employed conventional trend methods are linear regression (LR) and Mann-Kendall (MK) trend tests. These methods are often subject to inconsistent results with respect to the extent of changes reported in rainfall patterns. This study utilizes the advanced LR i.e., quantile regression (QR) and the modified MK (m-MK) trend methods to investigate the retrospective rainfall characteristics and associated trends for multi-temporal periods i.e., long-term (1951–2020), bifurcated (pre-1985 and post-1985), and most-recent (2000–2020), over different climate zones of India. Furthermore, temporal evolution and trend consistency (stability) were examined by comparing multi-temporal slope coefficients at various quantiles (τ) of rainfall distribution. The long-term trends in general rainfall characteristics (GRCs) exhibited drying patterns, while opposite increasing trends were observed in extreme rainfall characteristics (ERCs) for most of the study region. The results of QR at median tail (τ = 0.5) were more or less consistent with the results of m-MK test. Interestingly, an increase in the trend significance and magnitude was observed at higher quantiles (τ > 0.8). The bifurcated and long-term periods showed contrasting results in rainfall characteristics, suggesting trend instability whereas during pre-1985, post-1985, and most-recent periods, the temporal evolution of GRCs revealed a systematic increment in positive trend significance. Altogether, the advanced and modified trend assessment in the present research compliments conventional trend methods with improved trend detection and trend consistency identification.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (Germany)

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21

Similar content being viewed by others

Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author (email: ankittandon@cuhimachal.ac.in) on reasonable request.

References

Download references

Acknowledgements

The Authors gratefully acknowledge the Indian Meteorological Department (IMD) for providing gridded daily rainfall data over India. The first author would like to express his appreciation to Central University of Himachal Pradesh for providing lab facilities and financial assistance in the form of Ph.D. fellowship. CK acknowledges the University Grants Commission, India, for Junior Research fellowship.

Author information

Authors and Affiliations

Authors

Contributions

Ashish Dogra: conceptualization, methodology, data curation, formal analysis, visualization, writing—original draft preparation, writing—reviewing and editing the manuscript; Chhabeel Kumar: data curation, visualization; Ankit Tandon: supervision, conceptualization, writing—reviewing and editing the manuscript.

Corresponding author

Correspondence to Ankit Tandon.

Ethics declarations

Ethics approval

All authors read and approved the final manuscript.

Consent to participate

All authors have agreed to participate.

Consent for publication

All authors have agreed to publication.

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Dogra, A., Kumar, C. & Tandon, A. Utilizing advanced and modified conventional trend methods to evaluate multi-temporal variations in rainfall characteristics over India. Theor Appl Climatol 155, 371–397 (2024). https://doi.org/10.1007/s00704-023-04640-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00704-023-04640-9

Navigation