Seasonal analysis of long-term (1970–2020) rainfall variability using clustering and wavelet transform approach in the Mahi River Basin, India

Understanding the trend of seasonal rainfall in the context of climate change is crucial for the maintenance of regional water resources management. The present study examines the seasonal rainfall trend in the Mahi River basin, India by using the wavelet transform and clustering method. Daily gridded rainfall data (0.25° × 0.25° spatial resolution) for 51 grids from 1970 to 2020 have been taken from India Meteorological Department (IMD). The monthly, seasonal, and annual statistic has been analyzed for 51 years. We have also plotted the relationship between precipitation trend–elevation. After that, homogeneous precipitation regions are delineated with hierarchical clustering analysis. Results reveal that seasonal precipitation over the basin clusters into 4 subregions for monsoon and 3 subregions for winter, pre-monsoon, and post-monsoon seasons. After the regionalization of the subregions, the periodicity and the inter-seasonal relationship were analyzed using continuous wavelet transform (CWT). In addition, it was clear that the cross-correlation between pre-monsoon and monsoon seasons had a significant periodic change in the last 30 years over the basin. The basin is located adjacent to the Arabian sea, which makes the basin more sensitive to a natural event like ENSO, it can cause changes in ocean temperatures and atmospheric circulation patterns that affect precipitation patterns during the study period. It is expected that some natural phenomena like monsoon variability, low-level jet streams, and many more also have an impact on the rainfall patterns of the basin. Thus, the understanding of seasonal precipitation variation provides a practical reference for water resources management, agricultural planning, and a forecast of precipitation in different regions and river basins of India which may give a better climate change indication.