Abstract
The paper analyzed the spatial-temporal variability of rainfall and detection of potential trend change point over Kosi River basin, Kumaon Lesser Himalaya, India, using long-term gridded data and historical metrological records in hilly river basin of Uttarakhand. The Mann-Kendall (MK) test was used to determine the spatio-temporal trend using IMD (0.25° × 0.25°) gridded rainfall data during 1901–2015. The Theil-Sen slope was used to determine the magnitude of change in rainfall during the study period. Additionally, the sequential Mann-Kendal (SQ-MK) test and Pettitt’s test has been used to find the abrupt change point in historical time series (1980–2019). Results of the study show that northeastern and southwestern parts of the Kosi River basin exhibit a statistically significant decreasing trend in both June and July months at 5% significance level. Northeastern and southwestern parts of the basin exhibit a statistically significant decreasing trend for monthly and annual rainfall. The range of Sen’s slope values varies from −0.6 to −6.6 mm/year. Based on the analysis of SQ-MK and Pettitt’s test, the change points for Almora, Mukteshwar, and Hawalbagh were 1991, 2004, and 1998 respectively. Therefore, this paper attempts to provide actionable knowledge for irrigation water planning, water management, and soil and water conservation for Uttarakhand.









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Acknowledgements
This work is carried out as P.hD’s thesis work at Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi. The authors thankfully acknowledge the ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan, Almora, Uttarakhand, for providing financial support and Division of Agricultural Engineering, ICAR-Indian Agricultural Research Institute, New Delhi, for providing necessary facilities during the course of investigation.
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Kumar, U., Singh, D.K., Panday, S.C. et al. Spatio-temporal trend and change detection of rainfall for Kosi River basin, Uttarakhand using long-term (115 years) gridded data. Arab J Geosci 16, 173 (2023). https://doi.org/10.1007/s12517-023-11244-0
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DOI: https://doi.org/10.1007/s12517-023-11244-0