STUDY ON LONG TERM VARIATION OF HYDROMETEOROLOGY DATA AND CORRELATION AND CAUSALITY OF GROBAL SCALE PHENOMENA IN UNITED BENGAL REGION

<p> Bangladesh is one of the most disaster-prone countries in the world, with great negative consequences being associated with various natural and human-induced hazards. Therefore, the evaluation of long-term variation of recorded meteorological and hydrological time-series data is necessary for infrastructure development in the future. In this study, we collected the 32 years monthly precipitation data at 36 locations in Bangladesh, the 116 years monthly precipitation data at 7 areas in India using and 30 years data of the daily water level at 4 locations in the Ganges Brahmaputra Meghna and Haor in Bangladesh. We have conducted the trend analysis by using these data and also conducted the correlation and causality analysis in order to find the relation to global scale phenomena such as SOI and DMI. We employed Mann-Kendall test and Seasonal Mann-Kendall test for long-term trend test of precipitation and river water level, the wavelet and cross-wavelet coherence analysis for correlation and VAR-LiNGAM for causality between the precipitation and SOI, the precipitation and DMI.</p><p> From the Mann-Kendall test and Seasonal Mann-Kendall test a significant decrease trend in the central part of Bangladesh is shown. Meanwhile the decrease trend with no significant is shown in northern part and no trend is shown in the other part. It is found that the slope of trend in 32 years is bigger than that in 116 years from the data of India. The daily water level of three major rivers have significant decrease trend in recent 30 years. Especially, the slope of the trend in Brahmaputra is bigger than the others. For the relation to global scale phenomena, the cross-wavelet coherence analysis shows the correlation of DMI to monthly precipitation is stronger than that of SOI. The causality from DMI to precipitation in Bengal area with 5 to 6 months lag is found by VAR-LiNGAM analysis.</p>