Stochastic multi-site generation of daily rainfall occurrence in south Florida |
| |
| Authors: | Tae-woong Kim Hosung Ahn Gunhui Chung Chulsang Yoo |
| |
| Institution: | (1) Department of Civil and Environmental System Engineering, Hanyang University, Gyeonggi-do, 425-791, South Korea;(2) U.S. Nuclear Regulatory Commission, Mail Stop O9E3, Washington, DC 20555, USA;(3) Department of Civil Engineering and Engineering Mechanics, The University of Arizona, Tucson, AZ 85721, USA;(4) Department of Civil and Environmental Engineering, Korea University, Seoul, 136-701, South Korea |
| |
| Abstract: | This paper presents a stochastic model to generate daily rainfall occurrences at multiple gauging stations in south Florida.
The model developed in this study is a space–time model that takes into account the spatial as well as temporal dependences
of daily rainfall occurrence based on a chain-dependent process. In the model, a Markovian method was used to represent the
temporal dependence of daily rainfall occurrence and a direct acyclic graph (DAG) method was introduced to encode the spatial
dependence of daily rainfall occurrences among gauging stations. The DAG method provides an optimal sequence of generation
by maximizing the spatial dependence index of daily rainfall occurrences over the region. The proposed space–time model shows
more promising performance in generating rainfall occurrences in time and space than the conventional Markov type model. The
space–time model well represents the temporal as well as the spatial dependence of daily rainfall occurrences, which can reduce
the complexity in the generation of daily rainfall amounts. |
| |
| Keywords: | Daily rainfall Occurrence Markov process Space– time model |
| 本文献已被 SpringerLink 等数据库收录！ |
|
