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EN
Climate variability analysis is essential for predicting the behavior of various extreme weather events and making communities resilient. Notwithstanding the profound concerns, climate variability assessment faces numerous challenges due to inadequate and sometimes unavailability of data at spatiotemporal scales. This study makes an attempt to analyse climate variability in the Bhagirathi Sub-basin of India. Six meteorological variables were analysed from fourteen weather stations located in the Sub-basin during 1968–2017. Modified Mann–Kendall test was employed to ascertain the trends in meteorological variables. One-way ANOVA was used to assess the relationship between and within the variables. A total of 432 households were selected for reaffirming climate variability and impact on landscape. Significant trends were detected in highest maximum, mean maximum (Mmax) and mean minimum (Mmin) temperatures, relative humidity (Rh), rainfall and vapour pressure (Vp) at annual and seasonal scales. Stations located in eastern and deltaic Sub-basins registered varying trends in these meteorological variables due to anthropogenic activities-induced land use changes. ANOVA revealed a robust relation among rainfall, Vp, Mmin and Mmax. Perceptions of the sampled households revealed that climate variability has considerably affected food intensity, vegetation, soil, water resources and agricultural pattern. We find modified Mann– Kendall method effective in analysing climate variability in the Sub-basin. Thus, this method can be utilized for effective analysis of climate variability at spatial scales in geographical regions.
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