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Analyzing an Extreme Rainfall Event in Himachal Pradesh, India, to Contribute to Sustainable Development

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  • Nitin Lohan

    (Department of Applied Mathematics, Gautam Buddha University, Greater Noida 201312, India
    India Meteorological Department, Ministry of Earth Sciences (MoES), New Delhi 110003, India)

  • Sushil Kumar

    (Department of Applied Mathematics, Gautam Buddha University, Greater Noida 201312, India)

  • Vivek Singh

    (Indian Institute of Tropical Meteorology, (New Delhi Branch), Ministry of Earth Sciences (MoES), New Delhi 110060, India)

  • Raj Pritam Gupta

    (Department of Earth and Environmental Sciences, Indian Institute of Science Education and Research Bhopal, Bhauri 462066, India)

  • Gaurav Tiwari

    (Center for Environmental Remote Sensing, Chiba University, Chiba 2630022, Japan)

Abstract

In the Himalayan regions of complex terrains, such as Himachal Pradesh, the occurrence of extreme rainfall events (EREs) has been increasing, triggering landslides and flash floods. Investigating the dynamics and precipitation characteristics and improving the prediction of such events are crucial and could play a vital role in contributing to sustainable development in the region. This study employs a high-resolution numerical weather prediction framework, the weather research and forecasting (WRF) model, to deeply investigate an ERE which occurred between 8 July and 13 July 2023. This ERE caused catastrophic floods in the Mandi and Kullu districts of Himachal Pradesh. The WRF model was configured with nested domains of 12 km and 4 km horizontal grid resolutions, and the results were compared with global high-resolution precipitation products and the fifth-generation European Centre for Medium-Range Weather Forecasts atmospheric reanalysis dataset. The selected case study was amplified by the synoptic scale features associated with the position and intensity of the monsoon trough, including mesoscale processes like orographic lifting. The presence of a western disturbance and the heavy moisture transported from the Arabian Sea and the Bay of Bengal both intensified this event. The model has effectively captured the spatial distribution and large-scale dynamics of the phenomenon, demonstrating the importance of high-resolution numerical modeling in accurately simulating localized EREs. Statistical evaluation revealed that the WRF model overestimated extreme rainfall intensity, with the root mean square error reaching 17.33 mm, particularly during the convective peak phase. The findings shed light on the value of high-resolution modeling in capturing localized EREs and offer suggestions for enhancing disaster management and flood forecasting.

Suggested Citation

  • Nitin Lohan & Sushil Kumar & Vivek Singh & Raj Pritam Gupta & Gaurav Tiwari, 2025. "Analyzing an Extreme Rainfall Event in Himachal Pradesh, India, to Contribute to Sustainable Development," Sustainability, MDPI, vol. 17(5), pages 1-17, February.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:5:p:2115-:d:1602484
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    References listed on IDEAS

    as
    1. Sourabh Garg & Gaurav Tiwari & Sarita Azad, 2024. "Evaluation of the WRF model for a heavy rainfall event over the complex mountainous topography of Mandi, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(3), pages 2661-2681, February.
    2. Christoph Schär & Nikolina Ban & Erich M. Fischer & Jan Rajczak & Jürg Schmidli & Christoph Frei & Filippo Giorgi & Thomas R. Karl & Elizabeth J. Kendon & Albert M. G. Klein Tank & Paul A. O’Gorman & , 2016. "Percentile indices for assessing changes in heavy precipitation events," Climatic Change, Springer, vol. 137(1), pages 201-216, July.
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