CONSTRUCTION OF A PROBABILISTIC MODEL FOR SHORT-TERM HEAVY RAIN AND ITS APPLICATION TO RISK ASSESSMENT ON UNDERGROUND INUNDATION

Abstract

 A new probabilistic approach is applied to analyze the effect of temporally random variation of rainfall intensity associated with short-term heavy rain on randomness of rainfall inflow into an underground space, in which an approach is further discussed on risks of underground inundation.

 First, a probabilistic model is constructed for random behavior of rainfall intensity of short-term heavy rain by the use of a stationary Gaussian process for describing fluctuation around mean behavior. Then, based upon the probabilistic model, samples of hyetographs are generated on computer, which are transformed into samples of hydrographs through software package InfoWorks ICM. Next, a statistical approach is applied to analyze probability distribution of peak rainfall inflow. The result indicates that Weibull distribution or Gaussian distribution can well reproduce the random distribution of peak rainfall inflow, in comparison with log normal and Gumbel distributions. Further, a systematic approach is proposed on quantifying risk of underground inundation based upon the estimated probability distribution.