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中国农学通报 ›› 2026, Vol. 42 ›› Issue (20): 127-132.doi: 10.11924/j.issn.1000-6850.casb2026-0250

• 资源·环境·生态·土壤·气象 • 上一篇    下一篇

兴化蟹苗投放气象适宜期预报模型研究

章雯1(), 向阳1, 王琴1, 王喜1, 吴芳2, 季雅菲3, 袁昌洪1()   

  1. 1 泰州市气象局, 江苏泰州 225300
    2 兴化市气象局, 江苏兴化 225700
    3 靖江市气象局, 江苏靖江 214500
  • 收稿日期:2026-04-02 修回日期:2026-07-20 出版日期:2026-10-25 发布日期:2026-10-26
  • 通讯作者:
    袁昌洪,男,1971年出生,江苏姜堰人,正高级工程师,博士,主要从事农业气象研究。通信地址:225300 江苏省泰州市海陵区海陵南路299号 泰州市气象局,Tel:0523-86891121,E-mail:。
  • 作者简介:

    章雯,女,1997年出生,江苏姜堰人,工程师,硕士,主要从事天气预报研究。通信地址:225300 江苏省泰州市海陵区海陵南路299号 泰州市气象局,Tel:0523-86891121,E-mail:。

  • 基金资助:
    泰州市科技支撑计划(现代农业)项目“河蟹养殖水草管护气象服务关键技术研究与应用”(TN202509)

A Forecasting Model for Meteorological Suitable Period of Crab Seed Stocking in Xinghua

ZHANG Wen1(), XIANG Yang1, WANG Qin1, WANG Xi1, WU Fang2, JI Yafei3, YUAN Changhong1()   

  1. 1 Taizhou Meteorological Bureau, Taizhou, Jiangsu 225300
    2 Xinghua Meteorological Bureau, Xinghua, Jiangsu 225700
    3 Jingjiang Meteorological Bureau, Jingjiang, Jiangsu 214500
  • Received:2026-04-02 Revised:2026-07-20 Published:2026-10-25 Online:2026-10-26

摘要:

本文利用1991—2024年兴化河蟹养殖区的站点观测数据,采用逐步回归方法建立气象因子与蟹苗投放首日之间的预报模型,旨在为河蟹养殖提供精准的蟹苗投放期选择,以规避低温风险,从而提高成活率。研究发现:1991—2024年,兴化蟹苗的平均投放首日出现在2月21日(平年)/2月22日(闰年),呈现出逐年提前的趋势,提前速率为0.09 d/a;蟹苗投放前期的旬平均气温、降水量和日照时数与投放首日存在显著相关性;通过逐步回归分析,筛选出1月下旬日照时数、3月上旬极端最低气温和上年9月中旬极端最高气温这3个关键气象因子,建立蟹苗投放首日和前期气象因子预测模型,该模型对1991—2015年的数据拟合较好,对2016—2024年的预测值与实际值最小误差为0.76 d,模型预测结果平均误差为3.65 d。该模型预测结果具有较高的可信度,能够更好地服务于河蟹养殖生产。

关键词: 河蟹养殖, 蟹苗投放, 气象适宜期, 预报模型

Abstract:

Based on the observation data from monitoring stations in the Xinghua river-crab aquaculture area from 1991 to 2024, this paper established a forecasting model between meteorological factors and the first-day stocking of crab seedlings using the stepwise regression method. It provides technical support for river-crab farmers to avoid low-temperature risks and select accurate stocking periods so as to improve the survival rate of crab seedlings. The results showed that from 1991 to 2024, the average first stocking date in Xinghua fell on February 21 (in common years) or February 22 (in leap years), with a trend of advancing over time at a rate of 0.09 days/year. The ten-day mean temperature, precipitation, and sunshine duration prior to the stocking period were significantly correlated with the first stocking date. Using stepwise regression, three key factors were identified, including sunshine duration in late January, extreme minimum temperature in early March, and extreme maximum temperature in mid-September of the previous year, to construct a prediction model for the first stocking date based on preceding meteorological factors. The model demonstrated good fitting performance for the data of 1991-2015; for the year of 2016-2024, the minimum error between predicted and actual values was 0.76 days, with an average prediction error of 3.65 days. The model results are reasonably reliable and can better serve crab farming production.

Key words: crab farming, crab seed stocking, meteorological suitable period, forecasting model

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