现代经济高度依赖高压输电网络，但该基础设施频繁遭受地震、洪水、龙卷风和地磁暴等自然灾害的破坏。传统风险评估通常孤立地分析各类灾害，因而缺乏统一基准以比较全灾种组合下的经济损失。本研究通过构建一个整合框架弥补这一空白，该框架耦合灾害表征、脆弱性建模与宏观经济影响传播模型。该框架被一致应用于九类主要单一灾害及一类复合型冻雨—强阵风灾害。基于国家级灾害数据集，以及包含逾13,000条线路段和10,000座变电站的美国高压输电网络，我们推导出故障概率、预期损失、受影响人口及下游经济产出损失。在各类单一灾害中，热带气旋大风导致的日均预期损失最高，达1.37亿美元/天；其次为雷击（8700万美元/天）、地震（4700万美元/天）、洪水（4600万美元/天）、龙卷风（4200万美元/天）和滑坡（3400万美元/天）。下游经济产出损失最大的是龙卷风（49.3亿美元/天），其次为洪水（35.9亿美元/天）和地震（30.2亿美元/天）。一次250年一遇的地磁暴将造成20.7亿美元/天的损失，表明空间天气事件的影响已处于重大陆地灾害量级范围之内。复合型冻雨—强阵风情景则构成最严峻的压力测试情形，影响人口达2.374亿，并导致建模估算的下游经济产出损失高达851.6亿美元/天。上述结果应视为一阶边界估计值，其中复合情景代表一种上限压力测试。总体而言，该框架为跨灾种优先配置输电网络韧性投资建立了统一基准。

Modern economies depend critically on high-voltage power transmission networks. Yet this infrastructure is routinely disrupted by natural hazards ranging from earthquakes and floods to tornadoes and geomagnetic storms. Risk assessments have historically addressed hazards in isolation, leaving no common basis for comparing economic impacts across the full hazard portfolio. This study addresses this gap by developing an integrated framework linking hazard characterization, fragility modeling, and macroeconomic impact propagation. The framework is applied consistently across nine primary hazards and one compound freezing rain and wind gust hazard. Using national hazard datasets and a US high-voltage transmission network of over 13,000 line segments and 10,000 substations, we derive failure probabilities, expected damage, affected population, and downstream economic output losses. Among individual hazards, tropical cyclone wind produces the largest expected daily damage at $137 M/day, followed by lightning at $87 M/day, earthquake at $47 M/day, flood at $46 M/day, tornado at $42 M/day, and landslide at $34 M/day. Downstream economic output losses are largest for tornado at $4.93 B/day, followed by flood at $3.59 B/day and earthquake at $3.02 B/day. A 250-year geomagnetic storm produces $2.07 B/day, placing space weather within the range of major terrestrial hazards. The compound freezing rain and wind gust scenario produces the largest stress-test disruption, affecting 237.4 M people and yielding a modeled downstream output loss of $85.16 B/day. These results should be interpreted as first-order bounding estimates, with the compound scenario representing an upper-bound stress test. Overall, the framework establishes a consistent baseline for prioritizing investments in transmission network resilience.