有效降水指数在暴雨洪涝监测和评估中的应用

doi:10.3969/j.issn.1000-6362.2016.01.011

摘要/Abstract

摘要：

科学有效的监测和评估是防范和减轻暴雨洪涝灾害的重要基础。基于有效降水指数(EP)构建单站和区域暴雨洪涝监测、评估指标，利用1961-2014年湖北省76站逐日气象观测资料及相关灾情资料，确定降水衰减参数及致涝阈值，在此基础上分析EP指数在历史暴雨洪涝评估及实时暴雨洪涝过程监测中的应用效果。结果表明：经参数率定后的EP指数对农作物洪涝受灾面积的解释方差达78.1%，对年际间暴雨洪涝强度差异反应敏感，能识别历史典型大涝年和严重洪涝年，在2014年实时暴雨洪涝过程监测中能直观诊断出一般性暴雨洪涝的起止时间和过程动态变化，但对局地性和间歇性发生的暴雨洪涝过程刻画不足。创建EP指数所需数据资料少、计算简便，可用于洪涝灾害历史排位、年景评价、灾情预评估、风险区划以及作物产量建模等。

关键词: 有效降水指数, 参数率定, 暴雨洪涝, 应用检验

Abstract:

Scientific and effective monitoring and assessment are significant to prevent and mitigate the rainstorm flood disasters. Based on the Effective Precipitation Index (EP), the indices for flood monitoring and assessment at both site and regional scales were established. Using daily meteorological data from 76 stations in Hubei province and disaster loss data related during 1961 to 2014, the decay parameter and critical rainfall were determined, and the performance of the index in historical rainstorm flood assessment and real-time monitoring was examined. The results showed that the calibrated EP index explained 78.1% variances of damaged crop area, and it was sensitive to identify typical extreme and severe flood year from 1961 to 2014. During the real-time rainstorm flood in 2014, the EP index showed a certain capability to determine the start, duration, and strength of each flood process, while there was disagreement for local and discontinuous flood processes. Generally, the EP index was simple in calculation, reasonable in analysis and easy in spread. So it had more advantages in rainstorm flood evaluation, such as historical ranking, annual climatic assessment, disaster loss pre-evaluation, risk zoning, as well as crop yield prediction.

Key words: Effective Precipitation Index, Parameter calibration, Rainstorm flood, Application validation

秦鹏程，刘敏，李兰. 有效降水指数在暴雨洪涝监测和评估中的应用[J]. 中国农业气象, 2016, 37(01): 84-90.

QIN Peng-cheng, LIU Min, LI Lan. Application of Effective Precipitation Index in Rainstorm Flood Disaster Monitoring and Assessment[J]. Chinese Journal of Agrometeorology, 2016, 37(01): 84-90.

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