Construction and application of the “integration of provincial, urban, and county-wide” geo-hazard meteorological risk warning system in Sichuan Province
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摘要:
提升地质灾害气象风险预警预报能力是地质灾害综合防治体系建设的主要内容之一。四川省自2003年起率先开展地质灾害气象风险预警工作。在长期实践基础上，于2019年开始重点在预警模型分析和建立、系统设计与实现、分级预警运行模式等方面进行了研究，创建了地质灾害预警模型库、“省市县一体化”地质灾害气象风险预警互联系统及分级预警机制。基本实现了基于雨量数据传输、预警模型分析运算、预警信息发布等“省市县一体化”平台的互联互通及分级预警的闭环管理，初步解决了市县缺平台、缺经费、缺技术的三缺问题及多头发布预警信息对基层造成的干扰问题。2023年四川省成功避险的案例中地质灾害气象风险预警发挥作用的占86%，有效减少了地质灾害造成的人员伤亡和财产损失。
Abstract:Improving the geo-hazard meteorological risk warning capabilities is an important component of the comprehensive prevention system for geological disasters. Since 2003, Sichuan Province has been carrying out geo-hazard meteorological risk warning work. Building on the previous foundation, research has been focused on the analysis and establishment of warning models, system design and implementation, and graded warning operation modes since 2019. A geo-hazard warning model library, an integrated geological disaster meteorological risk warning interconnection system at the provincial, municipal, and county levels, and a graded warning mechanism have been created. We have achieved closed-loop management of interconnection and graded early warning based on integrated platform such as rainfall data transmission, early warning model analysis and calculation, and early warning information release in province, cities, and counties. This has solved the three problems of lack of technology, capacity, and funding in cities and counties, as well as the interference caused by multiple early warning information releases on grassroots levels. In 2023, 86% of the successful risk avoidance cases in Sichuan Province were affected by meteorological risk warning, effectively reducing casualties and property losses caused by geo-hazard.
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Key words:
- geo-hazard /
- meteorological risk warning /
- warning model /
- warning system
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表 1 各预警区临界降雨阈值判据
Table 1. Critical rainfall threshold criterion for each early warning area
预警
分区预警等级 K B 预警
分区预警等级 K B Ⅰ 红色预警 −0.44 82.8 Ⅶ1 红色预警 −0.45 58.0 橙色预警 −0.44 60.9 橙色预警 −0.45 51.5 黄色预警 −0.44 43.7 黄色预警 −0.45 43.0 Ⅱ1 红色预警 −1.24 138.9 Ⅶ2 红色预警 −0.34 80.4 橙色预警 −1.24 92.4 橙色预警 −0.34 61.7 黄色预警 −1.24 66.1 黄色预警 −0.34 43.3 Ⅱ2 红色预警 −0.79 76.1 Ⅷ1 红色预警 −0.53 36.6 橙色预警 −0.79 67.7 橙色预警 −0.53 35.5 黄色预警 −0.79 56.1 黄色预警 −0.53 34.7 Ⅲ1 红色预警 −0.23 160.4 Ⅷ2 红色预警 −0.38 60.5 橙色预警 −0.23 70.1 橙色预警 −0.38 50.2 黄色预警 −0.23 59.8 黄色预警 −0.38 43.2 Ⅲ2 红色预警 −0.33 136.3 Ⅷ3 红色预警 −0.49 47.2 橙色预警 −0.33 95.8 橙色预警 −0.49 46.0 黄色预警 −0.33 58.4 黄色预警 −0.49 35.0 Ⅳ 红色预警 −0.50 51.6 Ⅸ1 红色预警 −0.15 36.2 橙色预警 −0.50 44.0 橙色预警 −0.15 32.9 黄色预警 −0.50 40.7 黄色预警 −0.15 27.1 Ⅴ1 红色预警 −0.41 122.5 Ⅸ2 红色预警 −0.31 71.4 橙色预警 −0.41 99.2 橙色预警 −0.31 58.5 黄色预警 −0.41 76.1 黄色预警 −0.31 42.1 Ⅴ2 红色预警 −1.42 171.3 Ⅹ1 红色预警 −1.31 45.9 橙色预警 −1.42 132.6 橙色预警 −1.31 40.9 黄色预警 −1.42 113.4 黄色预警 −1.31 40.4 Ⅵ 红色预警 −0.32 105.9 Ⅹ2 红色预警 −0.88 50.8 橙色预警 −0.32 70.4 橙色预警 −0.88 49.6 黄色预警 −0.32 51.4 黄色预警 −0.88 43.7 
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表 2 各潜势度分区内降水诱发因子量化赋值
Table 2. Quantitative assignment of precipitation-inducing factors in each potential degree zone
龙门山
断裂带有效雨量计算时间/d 3 有效雨量/mm <100 100～120 120～200 200～250 250～300 ≥300 归一化值（T） 0.2 0.4 0.7 0.8 0.9 1 川东 有效雨量计算天数/d 2 有效雨量/mm <120 120～180 180～400 ≥400 归一化值（T） 0.2 0.4 0.7 1
川南有效雨量计算天数/d 2 有效雨量/mm <50 50～80 80～120 120～150 150～200 ≥200 归一化值（T） 0.2 0.4 0.6 0.8 0.9 1 川西 有效雨量计算天数/d 3 有效雨量/mm <30 30～50 50～80 80～100 ≥100 归一化值（T） 0.2 0.3 0.5 0.8 1 川东北 有效雨量计算天数/d 2 有效雨量/mm <80 80～100 100～150 150～250 ≥250 归一化值（T） 0.2 0.3 0.5 0.8 1
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表 3 各潜势度分区内显式统计预警模型判据
Table 3. Explicit statistical early warning model criterion in each potential degree zone
预警等级 潜势度分区
预警指数（R）龙门山 断裂带 川东 川南 川西 川东北 不预警 ≤0.3 ≤0.3 ≤0.3 ≤0.1 ≤0.3 黄色预警 0.3～0.6 0.3～0.6 0.3～0.6 0.1～0.3 0.3～0.6 橙色预警 0.6～0.9 0.6～0.9 0.6～0.9 0.3～0.5 0.6～0.9 红色预警 ＞0.9 ＞0.9 ＞0.9 ＞0.5 ＞0.9
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