The study of frequency analysis is important to find the most suitable model that could anticipate extreme events of certain natural phenomena e.g., rainfall, floods, etc. The goal of this study is to determine the best-fit probability distributions in the case of maximum monthly rainfall using 30 years of data (1984-2013) from 35 locations in Bangladesh by using different statistical analysis and distribution types. Commonly used frequency distributions were applied. Parameters of these distributions were estimated by the method of moments and L-moments estimators. Three goodness-of-fit test statistics were applied. The best-fit result of each station was taken as the distribution with the lowest sum of the rank scores from each of the three test statistics. Generalized Extreme Value, Pearson type 3 and Log-Pearson type 3 distributions showed the largest number of best-fit results. Among the best score results, Generalized Extreme Value yielded the best-fit for 36% of the stations and Pearson type 3 and Log-Pearson type 3 each yielded the best-fit for 26% of the stations. The more practical result of this paper was that the 10-year, 25-year, 50-year and 100-year return periods of maximum monthly rainfall were calculated for all locations. The result of this study can be used to develop more accurate models of flooding risk and damage.

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A method of determining the retro-reflectance of retro-reflective materials used for building coatings is proposed in this article. In addition, the durability of retro-reflective materials over long-term outdoor exposure is also estimated. Retro-reflective materials are currently limited to use in specific purposes, such as road traffic signs in Japan. To consider their application as a building coating, it is also necessary to examine the thermal performance and durability of retro-reflective materials. We proposed a method of determining the retro-reflectance of retro-reflective materials (capsule retro-reflective material and prism retro-reflective material were used in this experiment) by experiment. To explore the durability of retro-reflective materials over long-term outdoor exposure, we measured the changes in solar reflectance and retro-reflectance of retro-reflective materials exposed to the outdoors over about 25 months. The solar reflectance of capsule retro-reflective material decreased from 0.69 to 0.51 and that of prism retro-reflective material decreased from 0.83 to 0.81. The retro-reflectance of capsule retro-reflective material decreased from 0.18 to near 0 (0.0072) and that of prism retro-reflective material decreased from 0.44 to 0.42. At the end of the test period, we cleaned the surface of the retro-reflective 1 Doctor Course, Graduate materials. Both of the retro-reflective materials recovered about 50% of the lost solar reflectance by cleaning. The retro-reflectance of capsule retro-reflective material increased by about 0.08 (46% recovered) by cleaning and that of prism retro-reflective material increased by only 0.01 (with 50% recovered) by cleaning. We concluded that the durability of prism retro-reflective material is better than that of capsule retro-reflective material for use on building coatings.

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