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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 - 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:在离散事件调查的趋势是不断变化的极端事件模式的研究是必不可少的。在干旱事件发生的到达间隔时间的时间趋势进行了检查横跨维多利亚,澳大利亚21个选测站。在本研究中,标准化降水指数(SPI)是适用于12个月的时间尺度,以确定干旱。甲干旱事件这里被定义为一个周期,其中所述SPI是连续负和达到-1.0或更小的值。通常情况下,非参数检验通常用于测试趋势,包括离散事件。然而,离散事件是因为零个值的存在或数据的非正常性不是恒定的。该方法适用于事件计数的长期记录,是基于泊松过程和标准线性回归的随机概念。总体来看,21个车站,15显示有统计学显著频率增加表明这些事件越来越频繁。只有一个站了显着效果。剩下的5个站显示事件之间的时间显著上升候任干旱越来越频繁。

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