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Climate Change Vulnerability Assessment of a River Basin on Precipitation Applying CMIP6 Climate Model

International Journal of Civil Engineering
© 2024 by SSRG - IJCE Journal
Volume 11 Issue 10
Year of Publication : 2024
Authors : Mahesh S. Waghmare, Shrishaila S. Shahapure, Upendra R. Saharkar
10.14445/23488352/IJCE-V11I10P101
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How to Cite?

Mahesh S. Waghmare, Shrishaila S. Shahapure, Upendra R. Saharkar, "Climate Change Vulnerability Assessment of a River Basin on Precipitation Applying CMIP6 Climate Model," SSRG International Journal of Civil Engineering, vol. 11,  no. 10, pp. 1-20, 2024. Crossref, https://doi.org/10.14445/23488352/IJCE-V11I10P101

Abstract:

The hydrological impact is evaluated by downscaling huge-scale climate variables (predictors) simulated and modelled by a Global Climate Model. Hydro-meteorological variations illustrate the use of the Statistical Downscaling technique to enhance precipitation resolution. In this investigation, we introduce a statistical precipitation model utilizing three distinct approaches that are the Delta technique, the Quantile Mapping technique, and the Empirical Quantile Mapping technique. To investigate the statistical downscaling method, the weather stations Chaskaman, Paragon, Sakhar, and Shirur were chosen as research sites to evaluate the approach for precipitation. All the stations are situated within the Bhima River Basin. To identify patterns from historical observations and subsequently apply them to both historical and Shared Socioeconomic Pathway (SSP) periods (Shared Socioeconomic Pathway to describe possible future development). Future projections based on climate scenarios utilize CMIP6 data and the global climate model CNRM-CM6-1. The statistical downscaling results indicate that the SDGCM (Statistical Downscaling Global Climate Model) performs best in predicting daily precipitation. In the future period (2021-2100), the SDGCM model predicts an increase in average yearly rainfall at all four locations in the context of SSP245 and a substantial rise in average yearly rainfall at all four locations in the context of SSP585.

Keywords:

Climate change, GCMs, Rainfall, SDGCM, Statistical downscaling.

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