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Image of Journal of Applied Nonlinear Dynamics
ISSN:2325-6192 (print)
ISSN:2325-6206 (online)
Journal of Environmental Accounting and Management
António Mendes Lopes (editor), Jiazhong Zhang(editor)
António Mendes Lopes (editor)

University of Porto, Portugal

Email: aml@fe.up.pt

Jiazhong Zhang (editor)

School of Energy and Power Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi Province 710049, China

Fax: +86 29 82668723 Email: jzzhang@mail.xjtu.edu.cn

Analysis of Southwest Monsoon Rainfall in the Capital City Delhi (India)

Journal of Environmental Accounting and Management 13(4) (2025) 361--384 | DOI:10.5890/JEAM.2025.12.003

Ruma$^{1}$, Shashi Kant$^{2}$, Deepak Kumar$^{1}$

$^{1}$ Department of Applied Sciences, School of Engineering and Technology, Manav Rachna International Institute of Research and Studies, Faridabad, India

$^{2}$ India Meteorological Department, Ministry of Earth Sciences, New Delhi, India

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Abstract

Rainfall is not only crucial for life but also important for the balance of the natural hydrological cycle. This work studies the rainfall trend \& variability in the capital city of Delhi during the period $1990-2023$. A detailed analysis for rainfall at the scales of monthly, seasonal (June–September), and decade is done. The long-term trends in rainfall were determined by the Mann-Kendall test. The analysis revealed no trend in rainfall observed, which is not statistically significant for the whole summer monsoon season. The analysis for the decades $1990-2000$ and $2011-2023$ revealed a decrease in rainfall in both the periods and an increase in the decade $2001–2010$, but this was not statistically significant. It is found that in Delhi, the rainfall variability is the highest in June, followed by September and July. August rainfall showed the least variability. Comparing the mean rainfall with the climatology $(1991-2020)$, it is investigated that the mean rainfall slightly decreased by around 7 mm in the months of June \& August and increased in the months of July and September by about 17 mm and 13 mm respectively. In this study, the observed seasonal rainfall for the different return periods was also fitted by the statistical distributions Gumbel, Ven Te Chow, Log Pearson type III, and Log Normal for one to three consecutive days, and the best one was selected for the better prediction of maximum seasonal rainfall (JJAS) with respect to Chi-Square, Percentage Absolute Deviation (PAD), and Integral Square Error (ISE). It is investigated that the Gumbel distribution was the best fit, and the second best fit was Ven Te Chow for the goodness of fit for the prediction for one to three consecutive days of maximum seasonal rainfall in Delhi. This statistical analysis provides a strong foundation for future work on rainfall modeling and risk assessment in Delhi, helping to guide water resource management, urban planning, and infrastructure design under varying monsoon conditions.

Acknowledgments

Data collection, Concept, supervision \& reviewing by Shashi Kant; data analysis, writing initial draft by Ruma and supervision, reviewing \& editing by Deepak Kumar.

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