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Long term (1901−2021) trends and prediction of climatic variability in selected agro‐ecological zones of Himachal Pradesh using coupled statistical and machine learning approaches

Bibliographic Data

ID20153211
AuthorsSwati Thakur (0000-0001-9322-3411, Department of Geography, Dyal Singh College University of Delhi New Delhi India), Manish Kumar (0000-0002-1444-5508, Department of Geography, School of Basic Sciences Central University of Haryana Jant‐Pali, Mahendragarh Haryana India, corresponding author), Akash Tiwari (0000-0003-2840-1669, Department of Geography, School of Basic Sciences Central University of Haryana Jant‐Pali, Mahendragarh Haryana India), Ankur Yadav (0009-0006-3122-720X, Department of Geography, School of Basic Sciences Central University of Haryana Jant‐Pali, Mahendragarh Haryana India), Tamanna Soni (Department of Geography, School of Basic Sciences Central University of Haryana Jant‐Pali, Mahendragarh Haryana India), Dinesh Kumar Tripathi (0000-0002-7965-364X, Rana Pratap Post Graduate College Sultanpur Uttar Pradesh India)
Year2024
Volume45
Issue2
Pages384-402
Publication date2024-05-01
Open AccessYes
TypeARTICLE
VenueSingapore Journal of Tropical Geography (JOURNAL)
Journal identifiersISSN: 0129-7619 • E-ISSN: 1467-9493
PublisherWiley (PUBLISHER • GB)
DOI10.1111/sjtg.12530
OpenAlexW4391445850
LanguageEN
References cited24

This study analyses the trends of changing climatic elements in the hydrological regime of the Indian Himalayan Region with specific focus on Agro‐ecological zone II & III of Himachal Pradesh for the period of 1901−2021. The upper, middle, and lower catchment areas of Sutlej River Basin were studied to reveal regional trends in climatic parameters. The Mann‐Kendall test and Sen Slope analysis were used to estimate annual and seasonal trends and their magnitude. The results showed a significant decreasing trend in the lower catchment area, with a break point year estimated to be 1953 for the entire basin. Two blocks of analysis, 1901−1953 and 1954−2021, showed significant variations. Annual rainfall data revealed a statistically significant decreasing trend at different stations. The lower catchment area received a significant increase in rainfall compared to higher altitude stations. In terms of seasonal variation, the pre‐monsoon season showed a significant decrease, while the entire basin recorded a significant increase in average monthly temperature. The study concludes by generating future time series predictions using an ANN model for the period of 2022−2050. Overall, the study's findings indicate a significant change in climatic variables with signs of increasing monthly temperatures and decreasing annual rainfall

Biology · Geography · Physical geography · Statistics · Term (time) · Climate change impacts on agriculture · Ecology · Hydrological Forecasting Using AI · Hydrology and Drought Analysis · Mathematics

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