Abstract
The growing population in the community has led to an increase in the need for community infrastructure. Civil engineers have to maintain the safety of the community in the design of urban areas' service infrastructure. The infrastructure must resist the load caused by extreme events, such as rainstorms and floods. Therefore, civil engineers must design the infrastructure based on the precise data parameters. Engineers obtain the precise parameters of a return period through frequency analysis. The precise parameters will produce an acceptable data distribution. Civil engineers can use the Chi-Square method to test the fitness of the data distribution type. However, the original way to get the Expected Frequency is complicated because it uses the integral solving method. This weakness causes the engineers to linger to test the distribution suitability. This article proposes a modification to ease obtaining the expected frequency in the Chi-Square test. This article demonstrates the proposal using rainfall and river flow data around the globe. The demonstration results show that the proposal is easy to implement. The method accurately identifies the type of rainfall and river flow data distribution. Among the seven stations, five groups of data follow a lognormal distribution; one group of data follows a normal distribution. One other group of data follows an exponential distribution.