可视化降雨频率图集和暴雨高风险区划图集研究
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摘要
为了使降雨频率估算成果能够为涉水各行业的规划设计以及洪涝灾害预警和风险分析服务,并为大数据分析奠定科学基础,以厦门地区为例,首次使用包括水文及气象系统雨量站的年最大历史降雨资料,应用水文气象地区线性矩法以及暴雨高风险区划理论和技术,编制厦门地区降雨频率图集和暴雨高风险区划图集,研究降雨频率估计值的数字化以及暴雨高风险区划的可视化展示,建立估算成果的网络共享平台。考虑到暴雨频率估计值的不确定性,首次提供不同时段、不同重现期下频率估计值90%的置信区间,为风险分析提供科学依据。计算结果表明,厦门市东北部为暴雨高风险区;实际资料分析表明,厦门市西北角也可能存在一个暴雨高风险区,但是由于站点过少以及资料序列长度不够,建议今后资料充裕时进一步分析,这将对该地区雨量站的增设起到指导作用。
Precipitation frequency atlas & rainstorm high-risk regionalization atlas of Xiamen were established through utilizing the largest historical rainfall data from hydrological and meteorological stations for the first time and application of hydrometeorological homogeneous region linear moment method and rainstorm high-risk regionalization theory and technology. The work aimed to make the results of precipitation frequency estimation serve for the planning,design,flood disaster warning and risk analysis of various industries involved in water,and lay a scientific foundation for big data analysis in Xiamen. The precipitation frequency estimation was digitalized and the rainstorm high-risk regionalization was visualized,and a network sharing platform for the estimation results was established. Considering the uncertainties of the estimated precipitation frequency,the 90% confidence intervals for each period were provided to lay a scientific basis for risk analysis. The results indicated that the northeast of Xiamen was a rainstorm high-risk area. The analysis of actual data showed that the northwest of Xiamen was also a potential rainstorm high-risk area. However,due to the small number of stations and insufficient data sequence length,further analysis was suggested in the future when abundant data were available,which would play a guiding role in the establishment of rain stations in this region.
Precipitation frequency atlas & rainstorm high-risk regionalization atlas of Xiamen were established through utilizing the largest historical rainfall data from hydrological and meteorological stations for the first time and application of hydrometeorological homogeneous region linear moment method and rainstorm high-risk regionalization theory and technology. The work aimed to make the results of precipitation frequency estimation serve for the planning,design,flood disaster warning and risk analysis of various industries involved in water,and lay a scientific foundation for big data analysis in Xiamen. The precipitation frequency estimation was digitalized and the rainstorm high-risk regionalization was visualized,and a network sharing platform for the estimation results was established. Considering the uncertainties of the estimated precipitation frequency,the 90% confidence intervals for each period were provided to lay a scientific basis for risk analysis. The results indicated that the northeast of Xiamen was a rainstorm high-risk area. The analysis of actual data showed that the northwest of Xiamen was also a potential rainstorm high-risk area. However,due to the small number of stations and insufficient data sequence length,further analysis was suggested in the future when abundant data were available,which would play a guiding role in the establishment of rain stations in this region.
引文
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[9]Hosking J R M.L-moments:analysis and estimation of distributions using linear combinations of order statistics[J].J R Statist Soc B,1990,52(1):105-124.
[10]Hosking J R M,Wallis J R.Regional Frequency Analysis:An Approach Based on L-moments[M].Cambridge:Cambridge University Press,1997.
[11]Lin B,Bonnin G M,Martin D L,et al.Regional frequency studies of annual extreme precipitation in the United States based on regional L-moments analysis[A].EWRIProceedings[C].Omaha:ASCE-EWRI,2006.
[2]林炳章,邵月红,闫桂霞,等.水文气象促进工程水文计算核心课题研究的发展[A].2012中国水文学术讨论会论文集[C].南京:河海大学出版社,2012.Lin Bingzhang,Shao Yuehong,Yan Guixia,et al.Development of hydrometeorology in promoting research on the core project of engineering hydrological calculation[A].Proceedings of 2012 Chinese Symposium on Hydrology[C].Nanjing:Hohai University Press,2012(in Chinese).
[3]任伯帜,许仕荣,王涛.皮尔逊-Ⅲ型分布统计参数的确定[J].中国给水排水,2001,17(1):40-42.Ren Bozhi,Xu Shirong,Wang Tao.Determination of Pearson-Ⅲdistribution statistical parameters[J].China Water&Wastewater,2001,17(1):40-42(in Chinese).
[4]Lin B,Vogel J L.A comparison of L-moments with method of moments[A].Engineering Hydrology:Proceedings of the Symposium[C].New York:American Society of Civil Engineers,1993.
[5]陈元芳,沙志贵,顾圣华,等.可考虑历史洪水对数正态分布线性矩法的研究[J].河海大学学报:自然科学版,2003,31(1):80-83.Chen Yuanfang,Sha Zhigui,Gu Shenghua,et al.Study on L-moment estimation method with consideration of historical floods for log-normal distribution[J].Journal of Hohai University:Natural Sciences,2003,31(1):80-83(in Chinese).
[6]张静怡,徐小明.极值分布和P-Ⅲ型分布线性矩法在区域洪水频率分析中的检验[J].水文,2002,22(6):36-38.Zhang Jingyi,Xu Xiaoming.Test on L-moment estimation method for GEV and P-Ⅲdistribution in region flood frequency analysis[J].Journal of China Hydrology,2002,22(6):36-38(in Chinese).
[7]陈永勤,黄国如.基于线性矩法的东江流域区域枯水频率分析[J].应用基础与工程科学学报,2005,13(4):409-416.Chen Yongqin,Huang Guoru.Regional low flood frequency calculation with L-moments method at Dongjiang Basin[J].Journal of Basic Science and Engineering,2005,13(4):409-416(in Chinese).
[8]吴俊梅,林炳章,邵月红.地区线性矩法在太湖流域暴雨频率分析中的应用[J].水文,2015,35(5):15-22.Wu Junmei,Lin Bingzhang,Shao Yuehong.Application of regional L-moment analysis method in precipitation frequency analysis for Taihu Lake Basin[J].Journal of China Hydrology,2015,35(5):15-22(in Chinese).
[9]Hosking J R M.L-moments:analysis and estimation of distributions using linear combinations of order statistics[J].J R Statist Soc B,1990,52(1):105-124.
[10]Hosking J R M,Wallis J R.Regional Frequency Analysis:An Approach Based on L-moments[M].Cambridge:Cambridge University Press,1997.
[11]Lin B,Bonnin G M,Martin D L,et al.Regional frequency studies of annual extreme precipitation in the United States based on regional L-moments analysis[A].EWRIProceedings[C].Omaha:ASCE-EWRI,2006.
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