基于趋势和跳跃成分分析方法的太河流域降水量序列研究
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摘要
明晰水文时间序列的组成并基于此开展相关研究是一种科学的研究水文现象的方法,可减小因序列的随机性产生的影响。利用序列相关性分析方法对太河流域1979—2012年降水量序列的趋势和跳跃成分进行识别和显著性检验。结果显示,该序列具有上升趋势且显著,而跳跃成分存在于2002年但不显著。未来太河流域降水量有较大可能呈现逐年增多的趋势,流域水资源量将增加,可以一定程度地缓解人口增长带来的用水压力,但有一定的几率出现枯水年。所得结论对太河流域的水资源合理配置有一定的参考意义。
It is a scientific method to study the hydrological phenomena by understanding the components of the hydrological time series and carrying out relevant research, which can reduce the stochastic influence of the sequence. In this study, the precipitation sequence of Taihe River Basin from 1979 to 2012 were used, and the correlation analysis method was adopted to identified the trend and change points of the sequence, which should satisfy the significance test. The results showed that the precipitation sequence had a significant upward trend and a non-significant change point in 2002. In the future, the precipitation in Taihe River Basin is likely to increase year by year, and the number of water resources in the basin will increase,relieving the pressures of water supply and use brought by population growth. But there is a certain probability of a dry year. This paper provides certain reference value for the rational allocation of water resources in this basin.
It is a scientific method to study the hydrological phenomena by understanding the components of the hydrological time series and carrying out relevant research, which can reduce the stochastic influence of the sequence. In this study, the precipitation sequence of Taihe River Basin from 1979 to 2012 were used, and the correlation analysis method was adopted to identified the trend and change points of the sequence, which should satisfy the significance test. The results showed that the precipitation sequence had a significant upward trend and a non-significant change point in 2002. In the future, the precipitation in Taihe River Basin is likely to increase year by year, and the number of water resources in the basin will increase,relieving the pressures of water supply and use brought by population growth. But there is a certain probability of a dry year. This paper provides certain reference value for the rational allocation of water resources in this basin.
引文
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[2]王文圣,金菊良,丁晶.随机水文学(第三版)[M].北京:中国水利水电出版社,2015.
[3]桑燕芳,李鑫鑫,谢平,等.水文时间序列概率预报方法的通用构架[J].湖泊科学,2018,30(3):611-618.
[4]蔡继,丁华龙,董四方,等.深圳水库降水周期及趋势分析[J].人民珠江,2015,36(6):39-43.
[5]袁满,王文圣,叶濒璘.有序聚类分析法的改进及其在水文序列突变点识别中的应用[J].水文,2017,37(5):8-11.
[6]桑燕芳,王中根,刘昌明.水文时间序列分析方法研究进展[J].地理科学进展,2013,32(1):20-29.
[7]刘光文.皮尔逊III型分布参数估计[J].水文,1990,10(4):1-15.
[8]孙济良,秦大庸.水文频率分析通用模型研究[J].水利学报,1989,20(4):1-10.
[9]陈守煜.模糊水文学[J].大连理工大学学报,1988,28(1):93-97.
[10]陈守煜.水资源与防洪系统可变模糊集理论与方法[M].大连:大连理工大学出版社,2005.
[11]HENSE A.On the possible existence of a strange attractor for the Southern Oscillatio[J].Beitrage zur Atmospharen-physik,1987,60(1):34-47.
[12]权先璋,温权,张勇传.混沌预测技术在径流预报中的应用[J].华中理工大学学报,1999,27(12):41-43.
[13]SINGH V P.The use of entropy in hydrology and water resources[J].Hydrological Processes,1997,11(6):587-626.
[14]SINGH V P.Entropy-based parameter estimation in hydrology[M].Boston:Kluwer Academic Publishers,1998.
[15]Sonuga J O.Entropy principle applied to the rainfall-runoff process[J].Journal of Hydrology,1976,30(1):81-94.
[16]KUMAR P,FOUFOULA G E.Wavelet analysis for geophysical applications[J].Reviews of Geophysics,1997,35(4):385-412.
[17]姜世中,张宏.黄河上游高寒地区水文时间序列的小波特征[J].人民黄河,2006,28(4):26-27.
[18]王维.流域水文模型在山东省设计洪水计算中的适用性研究[D].泰安:山东农业大学,2017.
[19]肖玉华,郑春,张丽丽.淄博市太河水库流域污染源调查及对策[J].山东水利,2009(S2):45-47.
[20]王文圣,丁晶,金菊良.随机水文学[M].2版.北京:中国水利水电出版社,2008.
[21]丁晶,邓育仁.随机水文学[M].成都:成都科技大学出版社,1988.
[22]丁晶,刘权授.随机水文学[M].北京:中国水利水电出版社,1997.
[23]金光炎.水文水资源随机分析[M].成都:四川大学出版社,2007.
[24]李平日,侯日平.全球气候变暖及其对大环境的影响[J].人民珠江,2000,21(3):1-5.
[25]张素琴,任振球,李松勤.全球温度变化对我国降水的影响[J].应用气象学报,1994,8(3):333-339.
[26]陈操操,谢高地,甄霖.泾河流域降雨量变化特征分析[J].资源科学,2007,29(2):172-177.
[27]JAIN A,KUMAR AM.Hybrid neural network models for hydrologic time series forecasting[J].Applied Soft Computing,2007,7(2):585-592.
[28]山东省水文局.2002年山东省水资源公报[EB].2006.
[29]于浩.基于时间序列的延河流域水沙周期分析及趋势预测[D].杨凌:西北农林科技大学,2008.