This study assessed the spatio-temporal variability of soil loss based on rainfall–runoff erosivity in the context of climate change in the Kosi river basin. The observed rainfall data (1985–2017) were used for past and present analyses, and the projected rainfall data (2020–2100) interpolated for various general circulation models (GCMs) were used for future analysis. The results of rainfall analysis for the projected period show a maximum percentage variation of 26.2% for a particular GCM and an average of 9.4% increase in the rainfall data from all selected GCMs considering three representative concentration pathways (RCPs). We also evaluated the implications of change in the soil loss due to changes in the rainfall pattern and crop management factor for three time slices. The results for the projected time period showed a concomitant increase in the average soil loss of −13.03–10.39% with respect to the baseline. The average soil loss results for the time period of 2020–2100 are also compared with the average soil loss for each RCP scenario and found very meager changes in the area of soil erosion. The results due to climate change aid in prioritizing the areas with suitable conservation support practices.

Spatial and temporal analysis of rainfall data were carried out along with wavelet analysis for seven rain gauge sites of Kosi basin, India during the time period from 1985 to 2017. Wavelet spectrum analysis and wavelet coherence analysis were performed to fully characterize the time-frequency rainfall variability of the rain gauge data in these areas. For all the selected gauge stations during the study period, the peak value of the wavelet power spectrum was identified for the 8-16 month band. The results of wavelet spectrum analysis reveal a good correlation of rainfall data in the rain gauge sites lying in the southwest of the Kosi basin. The spectrum analysis also differentiates the wet and dry periods and it was observed that in the majority of the selected sites, a dry period occurred from the year 2005 onwards. This was again confirmed with breakpoint analysis. The wavelet coherence analysis explicit is a good correlation between the rain gauges in the study area. Overall, the variability of the rainfall parameters was more vivid with the wavelet analysis and this can be extended to other climatological parameters.

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