The present study measures management of flash flood to avoid the devastating impacts on boro rice production at Sunamganj district. This study interacts for meteorological parameter assessment with global climate data. Three major climatic parameters (precipitation, temperature and cloud fraction) have been considered for this study. These three climatic data were analyzed using numerical software EdGCM for the period 1920 to 2020 and then downscaled by Transform software. Flash floods have been classified as general flash floods and devastating flash flood. Flash floods have been reported to be severe in March and April. A trend was evaluated for the detection of flash flooding occurrences. The study concludes that when temperature is high, a small amount of rainfall can cause a slight cloud fraction to cause flooding. Flash flooding occurs when temperature is above 76oF(24.44oC), rainfall is at least 3 mm and cloud fraction is at most 46%. Furthermore, for validation Mann-Kendall trend analysis have been done. The test result discovered increasing trend for rainfall and decreasing trend for temperature and cloud fraction. Finally, an algorithm was developed in C++ program as a flash flood precaution tool which helped to prepare strategy as well as to adapt with the flash flood.

Downscaling is a state-of-the-art technique to generate fine-resolution climate change prediction and an obvious tool for forecasting future climate scenarios for many data-scarce areas like Bangladesh. The Educational Global Climate Model (EdGCM) predicts numerically and its performance was not evaluated for Bangladesh earlier. Due to this reason, an attempt has been made to apply a new geostatistical approach with the help of transform software to downscale EdGCM for identifying the trend of surface air temperature at the Sylhet district. Both Doubled_CO² and Global_Warming_01 are simulated from EdGCM and maps are generated to depict global temperature variations. Downscaling is applied to the outputs from Doubled_CO² scenario. Percent of bias (PBIAS), Nash-Sutcliffe efficiency (NSE) and the ratio of root mean square error to the standard deviation of measured data (RSR) values are satisfactory and acceptable. The trend analysis was performed using the Mann-Kendall Trend test and Sen’s slope estimator. Temperature changes are significant for both downscaled and observed results of p-value which is less than alpha = 0.05. Mann-Kendall Z tests for annual downscaled and IPCC during (2006-2020) show a positive trend. Downscaled predicted annual average temperature (simulations by Doubled_CO²) for 2020 is 21.67˚C for the Sylhet district.

Background The unpredicted pandemic disease COVID-19 first flared up adversely in Europe by imparting interminable force of infected and fatality cases to Italy. In late February 2020, the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in northern Italy and swiftly proliferated to the entire country, albeit continuous to date (23 March 2022) with a lesser extent of deadliness. Current review focused on the invasions and the associated consequences by SARS-CoV-2 during the period of March 2020–March 2022. Main body of the abstract Initially, the lethality and transmissibility of the novel virus made Italy stunned within 1 month, the number of death cases reached 12,428 at the end of March 2020. The Italian Government announced an immediate emergency phase in entire country, educational institutions to local businesses, manufacturing works, cultural activities to elective activities were rescinded and all the hospitals to morgues were swamped, ensuing that fear of epidemic was impended. Besides, the Italian National Health System and Service coordinated massive public health interventions and conferred unprecedented efforts to limit the high mortality rate of the first wave of infection. Amidst 2 years of epidemic (as of 23 March 2022), Italy has documented 14,070,450 (23.74% of the population) confirmed infected cases, 12,685,306 (21.41% of the population) healed cases, 158,254 death cases (0.27% of the population) and ranking 9th worldwide in the number of deaths. Short conclusion Based on publicly available Italian Ministry of Health COVID-19 data, current review has comprehended region-wise total infected cases, death cases and healed cases for three consecutive years 2020–2022 to foresee different patterns of the regional outbreak and gradual subservience. At a glance, we highlighted the overview of the exhaustion and exertion of COVID-19 crisis throughout the periods in Italy.

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