Open AccessCalculation of Early Warning Indicators for Small Watersheds Based on Mathematical Statistics
Author(s) -
Shiru Zhang,
Guoqing Sang
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/631/5/052001
Subject(s) - warning system , flood myth , flood warning , flooding (psychology) , watershed , flood forecasting , environmental science , precipitation , computer science , meteorology , hydrology (agriculture) , environmental resource management , statistics , geography , mathematics , geology , psychology , telecommunications , geotechnical engineering , archaeology , machine learning , psychotherapist
The early warning and forecasting of mountain flood disasters is an indispensable part of mountain flood prevention and control work. Reasonable selection of rainfall warning indicators is the key to mountain flood warning and forecasting work. This paper proposes a method for calculating the critical rainfall warning indicator based on mathematical statistics. That is, the characteristic period is determined based on the confluence time and watershed characteristics of the upstream watershed of the disaster prevention object. The stimulated rainfall of each characteristic period and its corresponding antecedent precipitation index is calculated based on the rainfall data of the flooding. Using the regression analysis method to draw the critical rainfall line, calculate the critical rainfall warning indicator and take the typical disaster prevention objects of Chahekou Village in Muping District of Yantai City, Shandong Province as an example, and the historical rainfall records of 2014-2018 were used as verification data to verify the early warning indicators. The results show that the critical rainfall accuracy calculated by this method is about 80%, which can provide reference for the application of early warning indicators for mountain flood disasters.