基于作物产量历史丰歉气象影响指数的河北省葡萄产量预报对比分析

doi:10.3969/j.issn.1673-503X.2025.02.011

Journal of Meteorology and Environment ›› 2025, Vol. 41 ›› Issue (2): 93-100.doi: 10.3969/j.issn.1673-503X.2025.02.011

• ARTICLES • Previous Articles

Comparative analysis of grape yield forecasting in Hebei province based on historical meteorological impact index of crop yield abundance

LI Ruiying^1,2,3,4, SUN Lihua^2,3,4, ZHOU Yanjun^2,3,4, WEI Anqi^2,3,4,5, WEI Ruijiang^3,6

1. CAM & China Re CRM Joint Open Lab on Meteorological Rish and Insurance, Beijing 100081, China;
2. Qinhuangdao Key Laboratory of Monitoring and Early Warning Technology for Severe Weather at Land-sea Boundary, Qinhuangdao 066000, China;
3. Hebei Provincial Meteorological and Eco-environmental Key Laboratory, Shijiazhuang 050021, China;
4. Qinhuangdao Meteorology Bureau, Qinhuangdao 066000, China;
5. Qinhuangdao Meteorological Disaster Prevention Center, Qinhuangdao 066000, China;
6. Meteorological Science Institute of Hebei Province, Shijiazhuang 050021, China

Received:2024-03-01 Revised:2024-04-08 Published:2025-06-20

Abstract

Abstract: This study utilizes grape yield data and corresponding meteorological data from Hebei province from 1981 to 2020.Based on the historical meteorological impact index of crop yield abundance,two methods-maximum probability method and weighted average method-were applied to develop grape yield forecasting models for dynamic yield prediction analysis.Model validation results show that the accuracy rates of yield abundance trend prediction were 77.8% and 84.4% for the maximum probability method and the weighted average method,respectively,while the quantitative forecasting accuracy rates were 83.1% and 90.3%,respectively.Model evaluation results indicated that during 15 yield abundance trend forecasts over 5 years,the maximum probability method had 5 errors,while the weighted average method had 3 errors,with quantitative forecasting accuracy rates of 89.9% and 94.0%,respectively.The weighted average method based on the historical meteorological impact index of crop yield abundance performed better in forecasting grape yield in Hebei province.

Key words: Maximum probability method, Weighted average method, Meteorological data, Dynamic forecasting

CLC Number:

S165⁺.27

LI Ruiying, SUN Lihua, ZHOU Yanjun, WEI Anqi, WEI Ruijiang. Comparative analysis of grape yield forecasting in Hebei province based on historical meteorological impact index of crop yield abundance[J]. Journal of Meteorology and Environment, 2025, 41(2): 93-100.

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Comparative analysis of grape yield forecasting in Hebei province based on historical meteorological impact index of crop yield abundance

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