TIME-SPACE CHARACTERIZATION OF PRECIPITATION IN THE GANGES-BRAHMAPUTRA-MEGHNA RIVER BASIN FOR PROJECTING RIVERBANK EROSION IN THE BANGLADESH OUTLET

Abstract

The Ganges-Brahmaputra-Meghna (GBM) river basin is the world’s third-largest river basin covering Nepal and Bhutan and certain parts of China, India, and Bangladesh. Literature show that changes in precipitation have a significant impact on climate, agriculture, and the environment in the GBM and many natural disasters such as drought, flood, landslides, and riverbank erosion are also a function of precipitation in the GBM river basin. Two satellite-based precipitation products, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and Multi-Source Weighted-Ensemble Precipitation (MSWEP), were used to study the relationship between seasonal precipitation as well as to analyze and compare precipitation trends over the GBM as a whole and for Pfafstetter level-05 sub-basins separately for the period 1983–2019. Positive correlations between precipitation within nearby hydrological sub-basins of the GBM were found during pre-monsoon and monsoon seasons. However, only two sub-basins of the GBM show a significant correlation between pre-monsoon and monsoon precipitation among 32 hydrological basins based on PERSIANN-CDR. The correlation between ENSO and seasonal precipitation was also studied. A higher negative correlation between ENSO and precipitation in the monsoon season was found than in the pre-monsoon season. A non-parametric Modified Mann-Kendall test was applied to determine significant trends in monsoon (June–September) and pre-monsoon (March–May) precipitation. The results show an inconsistency between the two precipitation products. However, both products strongly indicate that precipitation has recently declined in the pre-monsoon and monsoon seasons in the eastern and southern regions of the GBM river basin, agreeing with several previous studies. The results did not support precipitation as a predictive driver in causing riverbank erosion in coastal Bangladesh. The findings of the present study provide useful information for managing water crises, agricultural production, and preparing for different natural hazards in the GBM river basin.