Estimate of annual daily maximum rainfall and intense rain equation for the Formiga municipality, MG, Brazil

Knowledge of the probabilistic behavior of rainfall is extremely important to the design of drainage systems, dam spillways, and other hydraulic projects. This study therefore examined statistical models to predict annual daily maximum rainfall as well as models of heavy rain for the city of Formiga - MG. To do this, annual maximum daily rainfall data were ranked in decreasing order that best describes the statistical distribution by exceedance probability. Daily rainfall disaggregation methodology was used for the intense rain model studies and adjusted with Intensity-Duration-Frequency (IDF) and Exponential models. The study found that the Gumbel model better adhered to the data regarding observed frequency as indicated by the Chi-squared test, and that the exponential model best conforms to the observed data to predict intense rains.降雨概率分布特性的认知，对于排水系统、大坝溢洪道及其他水利工程的设计而言至关重要。因此，本研究针对Formiga - MG，探究了用于预测年日最大降雨量的统计模型以及强降雨模型。为此，研究人员将年日最大降雨量数据按降序排列，通过超越概率（exceedance probability）确定最适配该数据的统计分布形式。本研究采用日降雨分解方法开展强降雨模型研究，并结合强度-历时-频率（Intensity-Duration-Frequency, IDF）模型与指数模型进行校准调整。研究通过卡方检验（Chi-squared test）证实，耿贝尔模型（Gumbel model）更贴合观测频率对应的实测数据；而指数模型则最适配用于强降雨预测的实测数据。