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Prediction method of debris flow by logistic model with two types of rainfall: a case study in the Sichuan, China

机译:基于两类降雨的Logistic模型泥石流预测方法:以四川为例

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摘要

Debris flow is a serious disaster that frequently happens in mountainous area. This study presents an effective method for forecasting it by rainfall, which is one of the important components for prediction. The Sichuan Province is taken as an example. The geographic information system (GIS) is chosen as a tool to estimate the precipitation of hazard point, and use of statistical technique is made to calculate attenuation coefficient of effective antecedent precipitation. With such methodologies, the logistic regression model is used to comparatively establish the prediction model of two forms rainfall combination: (1) intraday rainfall and 10-day previous rainfall, (2) intraday rainfall and two types of effective antecedent rainfall which are short-time-heavy rainfall and long-time-light rainfall. The results indicate that the location of debris flows and the distribution of rainfall are factors interrelated. Secondly, the contribution rate of intraday rainfall is the highest. Thirdly, the second form rainfall combination has a higher prediction accuracy, 2.3% for short-time-heavy rainfall and 2.1% for long-time-light rainfall, which suggests that a moderate improvement is achieved by the rainfall classification.
机译:泥石流是在山区经常发生的严重灾害。本研究提出了一种有效的降雨预报方法,它是预报的重要组成部分之一。以四川省为例。选择了地理信息系统(GIS)作为估算灾害点降水的工具,并利用统计技术计算有效前期降水的衰减系数。通过这种方法,使用logistic回归模型比较地建立了两种形式的降雨组合的预测模型:(1)日内降雨和10天以前的降雨,(2)日内降雨和两种有效的前期降雨,即短期降雨。长时间降雨和长时间降雨。结果表明,泥石流的位置和降雨的分布是相互关联的因素。其次,日内降雨的贡献率最高。第三,第二种降雨组合具有较高的预测准确度,短时强降雨为2.3%,长时光降雨为2.1%,这表明通过降雨分类获得了适度的改善。

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