Estimation of critical streamflow discharge level using quantile regression approach

被引：0

作者：

Mwita, Peter N. ^{[1
]}

Franke, Juergen ^{[1
]}

机构：

[1] Jomo Kenyatta Univ Agr & Technol, Dept Math & Stat, PO Box 62000, Nairobi 00200, Kenya

来源：

PROCEEDINGS OF THE SIXTH IASTED INTERNATIONAL CONFERENCE ON MODELLING, SIMULATION, AND OPTIMIZATION: SCIENCE AND TECHNOLOGY FOR DEVELOPMENT IN THE 21ST CENTURY | 2006年

关键词：

streamflow; time series; quantiles; nonparametric regression; modelling;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Effective flood risk measures are important tools for river catchments' management. Among others, flood hazard mitigation programs and insurance companies can actively use these measures for reservoir operations, relief effort planning and premium setting, respectively. This work develops a nonparametric quantile regression approach for the estimation of flood quantiles conditional on past strearnflow discharges. The resulting estimator of conditional quantiles is found to be consistent and asymptotically normal. Real data from a streamflow gauging station in the Nyando Basin, Western Kenya, is used to demonstrate the potential of the approach.

引用

页码：177 / +

页数：3

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