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Temporal Trends of Discrete Extreme Events - A Case Study

机译:离散极端事件的时间趋势 - 以案例研究

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Investigating trends in discrete events is essential for the study of changing patterns of extreme events. Temporal trends in the inter-arrival times of occurrence of drought events were examined for 21 selected stations across Victoria, Australia. In the present study, the Standardize Precipitation Index (SPI) was applied for 12-month time scale to identify drought. A drought event here is defined as a period in which the SPI is continuously negative and reaching a value of -1.0 or less. Often, nonparametric tests are commonly used to test for trends including in discrete events. However, discrete events are not constant because of the presence of zero values or non-normality of data. The methodology applies to long-term records of event counts and is based on the stochastic concepts of Poisson process and standard linear regression. Overall, of the 21 stations, 15 showed statistically significant increasing frequency indicates those events are becoming more frequent. Only one station gave insignificant result. The remaining 5 stations showed the time between events was significantly increasing designates droughts are becoming less frequent.
机译:调查离散事件的趋势对于改变极端事件模式的研究至关重要。在维多利亚州维多利亚州的21个选定站检查了干旱事件发生际发生时间的时间趋势。在本研究中,将标准化降沉淀指数(SPI)应用于12个月的时间尺度以识别干旱。这里的干旱事件被定义为SPI连续负载且达到-1.0或更低的值的时段。通常,非参数测试通常用于测试包括在离散事件中的趋势。然而,由于存在零值或数据的非正常性,离散事件不是恒定的。该方法适用于事件计数的长期记录,基于泊松过程的随机概念和标准线性回归。总的来说,21站的总体上,15显示统计上显着的增加频率表明这些事件变得更加频繁。只有一站给出了微不足道的结果。剩下的5个站点显示事件之间的时间显着增加,指定干旱变得越来越频繁。

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