金沙江下游遥测雨量站数据质量研究
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摘要
随着水文自动测报技术的发展,越来越多的自记雨量站投入使用,而研究自记雨量站的数据质量对水利工程的运行具有重要意义。采用格拉布斯准则和K-medoids聚类方法对金沙江下游流域收集的2008～2015年遥测雨量站逐时降雨数据系列进行数据质量分析研究。结果显示,该方法在年累积雨量异常值的确定以及逐时降雨数据奇异点的寻找方面效果显著,能快速判别异常值和奇异点,且有统计学理论基础。所提出的方法为颗粒度越来越细的水文数据质量分析提供了一定参考依据。
Along with the development of automatic measurement and forecast technology, more and more automatic rainfall stations are put into operation. Analyzing the quality of data measured by automatic rainfall station is of great significance to the operation of water project. The analysis on the hourly rainfall series from telemetry rainfall stations in the lower reaches of the Jinsha River from 2008 to 2015 was carried out by using the Grubbs criterion and k-medoids clustering algorithm. Based on the statistical theory, the results showed that the methods have a remarkable effect in determining the abnormal value of annual accumulated rainfall and the singular points of hourly rainfall data. The method provides some references for hydrological data quality analysis that is changed by increasingly fine particles.
Along with the development of automatic measurement and forecast technology, more and more automatic rainfall stations are put into operation. Analyzing the quality of data measured by automatic rainfall station is of great significance to the operation of water project. The analysis on the hourly rainfall series from telemetry rainfall stations in the lower reaches of the Jinsha River from 2008 to 2015 was carried out by using the Grubbs criterion and k-medoids clustering algorithm. Based on the statistical theory, the results showed that the methods have a remarkable effect in determining the abnormal value of annual accumulated rainfall and the singular points of hourly rainfall data. The method provides some references for hydrological data quality analysis that is changed by increasingly fine particles.
引文
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[12] Gwo-Fong Lin, Ming-Jui Chang, Chian-Fu Wang. A Novel Spatiotemporal Statistical Downscaling Method for Hourly Rainfall[J]. Water Resour Manage , 2017(31):3465-3489.
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[15] 李朋军.遥测与虹吸雨量计降水数据对比分析[J].水科学与工程技术,2016(2):51-53.
[16] 杨旭,刘志武,李波.多源降水数据在长江上游流域比较研究[J].长江流域资源与环境,2016,25(1):131-139.
[2] 吴骞,吴绍春.基于离群分析的水位异常识别研究[J]. 硅谷,2010(24):45.
[3] 詹艳艳,徐荣聪.时间序列异常模式的K-均距异常因子检测[J].计算机工程与应用,2009,45(9):141-145.
[4] 张睿,周建中,肖舸,等.金沙江下游梯级和三峡梯级水电站群联合调度补偿效益分析[J].电网技术,2013,37(10):2738-2744.
[5] 高俊刚,吴雪,张镱锂,等.基于等级层次分析法的金沙江下游地区生态功能分区[J].生态学报,2016,36(1):134-137.
[6] 世界气象组织(WMO)著,赵珂经等译.水文实践指南[M].北京:水利电力出版社,1987.
[7] 熊艳艳,吴先球.粗大误差四种判别准则的比较和应用[J].大学物理实验,2010,23(1):66-68.
[8] 夏宁霞,苏一丹,覃希.一种高效的K-medoids聚类算法[J].计算机应用研究,2010,27(12):4517-4519.
[9] 周世兵,徐振源,唐旭清.新的K-均值算法最佳聚类数确定方法[J].计算机工程与应用,2010,46(16):27-31.
[10] 杨茂林,卢炎生.基于剪枝的海量数据离群点挖掘[J].计算机科学,2012,39(10):152-156.
[11] Roy S S , Rouault M. Spatial patterns of seasonal scale trends in extreme hourly precipitation in South Africa[J]. Applied Geography, 2013(39):151-157.
[12] Gwo-Fong Lin, Ming-Jui Chang, Chian-Fu Wang. A Novel Spatiotemporal Statistical Downscaling Method for Hourly Rainfall[J]. Water Resour Manage , 2017(31):3465-3489.
[13] 周国良,高唯清,黄昌兴.2016年我国极端暴雨事件浅析[J].中国防汛抗旱,2017,27(1):75-78,87.
[14] 赵超,包为民,瞿思敏,等.遥测系统降雨观测粗差修正研究[J].人民长江,2003,34(2):4-5,55.
[15] 李朋军.遥测与虹吸雨量计降水数据对比分析[J].水科学与工程技术,2016(2):51-53.
[16] 杨旭,刘志武,李波.多源降水数据在长江上游流域比较研究[J].长江流域资源与环境,2016,25(1):131-139.