Study on Synthetic Weather Index Insurance Based on the Optimal Relationship between Weather and Yield

文献类型： 外文期刊

第一作者： Wang, Yueqin

作者： Wang, Yueqin;Zhao, Sijian;Nie, Qian;Zhang, Qiao

作者机构：

关键词： Growth stages; Meteorological disasters; Millet; Optimized matching; Synthetic weather index insurance; Yield losses

期刊名称：PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER SCIENCE AND APPLICATION ENGINEERING (CSAE2019)

ISSN：

年卷期： 2019 年

页码：

收录情况： SCI

摘要： Climate change increases the risk of weather-related disaster, and weather index insurance (WII) can effectively divert and disperse meteorological risk. To improve the ability to assess and reduce regional weather risk, this study uses the following information: daily meteorological data from 1957 to 2015, time series data for per-unit area yield of millet from 1980 to 2015, and the results of current and previous studies of meteorological disasters in Wuzhai County, Shanxi Province, to determine the key meteorological disasters that affect millet yield at key growth stages. Considering the comprehensive influence of multiple meteorological disasters, this study compares historical yield losses and main disasters, followed by a construction of synthetic weather indices, such as the rainstorm index P1+, the frost index T4-, and the drought indices P1-, P2-, P3-, and P4-. An optimized matching method is introduced to produce the relationship model, using which daily meteorological and yield losses data are continuously matched and optimized. The relationship model is used to quantitatively evaluate the impact of weather indices on millet yield, and an evaluation of the simulation of meteorological risks is carried out. Ultimately, a synthetic WII product for millet is designed, and the premium rate and trigger values are given.

分类号：

  • 相关文献
作者其他论文 更多>>

微信小程序