Md. Abu Shahin, Md. Monimul Huq & Md. Ayub Ali
Generalized extreme value distribution was used in maximum monthly rainfall data of seven stations, Dhaka, Mymensingh, Chittagong, Comilla, Cox’s Bazar, Maijdicourt and Rangamati in Bangladesh. The rainfall data for all stations over the period 1960-2012 was collected from Bangladesh Meteorological Department, Agargaon, Dhaka, Bangladesh. The statistical tools, descriptive statistics, Jarque-Bera test, Mann-Kendall test, Augmented Dickey-Fuller test, Kwiatkowski-Phillips-Schmidt-Shin test, Phillips-Perron test, generalized extreme value distribution, L-moment method; likelihood ratio test, chi-square test, probability plot, and density plot were used. The maximum monthly rainfall showed high fluctuations with minimum and maximum values in Comilla andMymensingh.The rainfall data displayed non-linear trend and stationary in nature and therefore stationary extreme value distribution was considered. On the basis of shape parameter, the appropriate distribution of Dhaka, Chittagong, Maijdicourt and Rangamati stations followed Gumbel distribution, Cox’s Bazar station followed Weibull distribution, and Mymensingh and Comilla stations followed Frechet distribution. The return levels with 95% confidence interval for return period 5,10,50and100 years are estimated from stationary generalized extreme value distributionand found that the estimated return levels increase as the increase of return periods. The highest maximum monthly rainfall has found within 100 years for Dhaka, Comilla and Rangamati stations. But, Mymensingh, Chittagong, Cox-Bazar and Rangamati stations will need more than 100 years. These results are very useful for management of water by policy makers in Bangladesh.
Maximum monthly rainfall, Generalized extreme value distribution, Gumbel distribution, Frechet distribution, Weibull distribution.
Please cite this article as:
Md. Abu Shahin, Md. Monimul Huq & Md. Ayub Ali (2019). Modeling of annual maximum monthly rainfall using generalized extreme value distribution in Bangladesh. International Journal of Recent Research and Applied Studies, 6, 1(4), 15-24.