Research of using RF model to drought forecast on Huaihe River

3rd International Conference on Water Resource and Environment

地球科学;生态环境科学

Wu, J.^1 ; Chen, Y.F.^2

Water Resources Department of Hebei Province, Shijiazhuang

050000, China^1

College of Hydrological and Water Resource, Hohai University, Nanjing

210098, China^2

关键词: Classification and regression tree;    Classification models;    Drought modeling;    Huaihe river basins;    Model variables;    Nonlinear problems;    Prediction model;    Random forests;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/82/1/012016/pdf
DOI  :  10.1088/1755-1315/82/1/012016

学科分类：环境科学（综合）

来源: IOP

【 摘 要 】

Random Forest is a combination classification model based on classification and regression tree. RF model can deal with nonlinear problem, therefore, it is able to predict drought. In this paper, RF model is used to forecast drought on the Huaihe River Basin where more and more serious droughts occur. The runoff of twenty-one stations can reflect the overall drought level on Huaihe River. First, the drought has been divided into three levels depending on the SPI criteria. Then, the most important thirty factors are selected as model variables according to the Incnodepurity index after selecting preliminary screening sets. Furthermore, analysis of the drought level of the hydrological stations during the period from 1963 to 2013 is carried out with RF model. The result shows the average accuracy rate of prediction is 73%. The RF drought model is demonstrated as a new effective drought prediction model to reduce or eliminate the loss caused by drought.