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中国农学通报

中国农学通报 ›› 2023, Vol. 39 ›› Issue (30): 94-100.doi: 10.11924/j.issn.1000-6850.casb2022-0880

• 资源·环境·生态·土壤 • 上一篇    下一篇

黑龙江省玉米暴雨洪涝灾害风险评估研究

徐永清(), 刘赫男(), 刘春生, 张洪玲, 蒋慧亮   

  1. 黑龙江省气候中心，哈尔滨 150030
  • 收稿日期:2022-10-17 修回日期:2023-01-25 出版日期:2023-10-25 发布日期:2023-10-19
  • 通讯作者: 刘赫男，女，1983年出生，黑龙江双鸭山人，高级工程师，硕士，主要从事应用气候研究。通信地址：150030 黑龙江哈尔滨香坊区电碳路71号 黑龙江省气候中心，Tel：0451-55105880，E-mail：104547296@qq.com。
  • 作者简介:

    徐永清，男，1975年出生，黑龙江甘南人，高级工程师，硕士，主要从事应用气候研究。通信地址：150030 黑龙江哈尔滨香坊区电碳路71号 黑龙江省气候中心，Tel：0451-55105880，E-mail：。

  • 基金资助:
    中国气象局决策气象服务专题研究重点项目“黑龙江省智能化农业致灾气候事件决策服务系统”(JCZX2022002); 黑龙江省政府第一次全国自然灾害综合风险普查领导小组办公室普查专项“区域气象站参与下的异常降水致灾评估模型”(FXPC2021009)

Study on Risk Assessment of Maize Rainstorm and Flood Disaster in Heilongjiang Province

XU Yongqing(), LIU Henan(), LIU Chunsheng, ZHANG Hongling, JIANG Huiliang   

  1. Heilongjiang Climate Center, Harbin 150030
  • Received:2022-10-17 Revised:2023-01-25 Published-:2023-10-25 Online:2023-10-19

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摘要：

本文采用GIS空间分析技术，以致灾危险性、承灾体暴露性、脆弱性和防灾减灾能力评估为理论基础，进行黑龙江省玉米暴雨洪涝风险评估研究。玉米暴雨危险性评估指标包括孕灾环境影响和暴雨洪涝指数；玉米暴露性评估指标包括玉米单位面积产量和玉米耕种密度；玉米脆弱性评估指标包括受灾玉米面积占比和玉米直接经济损失占比；玉米防灾减灾能力包括除涝面积和人均GDP。评估过程中针对各因子量纲不同，采用均一化方法进行了处理。权重采用层次分析法和专家打分法确定。结果表明：黑龙江省暴雨洪涝高风险区分布在松嫩平原的西部和东部，大兴安岭北部和张广才岭南部地区为低风险区；暴露性较高区域主要集中在松嫩平原的西部，低易损区主要分布在大、兴安岭和张广才岭西部地区；松嫩平原西部为高敏感区，大兴安岭、张广才岭和三江平原地区为低敏感区；松嫩平原南部，具有高或较高的防灾减灾能力，大、兴安岭和张广才岭地区防灾减灾能力较低；黑龙江省玉米暴雨灾害高风险区主要分布在松嫩平原的西部和西北部地区，较高风险区主要分布在松嫩平原北部和东部，大、兴安岭和张广才岭地区为低风险区，较低风险区主要集中在松嫩平原与小兴安岭过度地区和三江平原。

关键词: 玉米, 暴雨灾害, 风险评估, 黑龙江省, GIS

Abstract:

Based on the assessment of disaster risk, exposure and vulnerability of disaster bearing bodies, and disaster prevention and reduction ability, this paper adopt GIS spatial analysis technology to carry out the risk assessment of maize rainstorm and flood in Heilongjiang Province. Disaster risk assessment indicators included rainstorm and flood index and disaster pregnant environmental impact index; the exposure assessment indexes of disaster bearing bodies included maize planting density and yield per unit area; vulnerability assessment indicators included the proportion of direct economic losses and the proportion of affected farmland; disaster prevention and mitigation capacity included waterlogging area and GDP per capita. In the evaluation process, the homogenization method was used to deal with the different dimensions of each factor. The weight was determined by the analytic hierarchy process and expert scoring method. The results showed that the high risk areas of rainstorm and flood in Heilongjiang Province were located in the west and east of Songnen Plain, while the north of Daxing’an Mountains and the south of Zhangguangcai Ridge were low risk areas; high exposure areas were mainly concentrated in the west of Songnen Plain, and low vulnerability areas were mainly distributed in the west of Daxing’an Mountains and Zhangguangcai Mountains; the western Songnen Plain was a highly sensitive area, while the Daxing’an Mountains, Zhangguangcai Mountains and Sanjiang Plain were low sensitive areas; in the south of Songnen Plain, the ability of disaster prevention and reduction was high or higher, while the ability of disaster prevention and reduction in Daxing’an Mountains and Zhangguangcai Mountains was low; the high risk areas of maize rainstorm disaster in Heilongjiang Province were mainly distributed in the west and northwest of the Songnen Plain. The relatively high risk areas were mainly distributed in the north and east of the Songnen Plain. The areas of the Daxing’an Mountains and the Zhangguangcai Mountains were low risk areas. The relatively low risk areas were mainly concentrated in the transitional areas of the Songnen Plain and the Xiaoxing’an Mountains and the Sanjiang Plain.

Key words: maize, rainstorm disaster, risk assessment, Heilongjiang Province, GIS