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蒙特卡罗法在嫩江流域汛期降雨量预测中的应用
  • 期刊名称:南水北调与水利科技. 2011, 9(3):28-32.(科技核心)
  • 时间:0
  • 分类:P457.6[天文地球—大气科学及气象学]
  • 作者机构:[1]长春市水资源管理办公室,长春130021, [2]吉林大学环境与资源学院,长春130021
  • 相关基金:国家自然科学基金项目(50879028);南京水利科学研究院水文水资源与水利工程科学国家重点实验室开放基金项目(2009491311);水沙科学与水利水电工程国家重点实验室开放研究基金项目(sklhse-2010-A102)
  • 相关项目:基于水文气象因素耦合作用的中长期径流预报机理及方法研究
中文摘要:

以蒙特卡罗理论为基础,采用P-Ⅲ型分布函数来概括流域汛期降雨量的概率特性,并以包含预测值样本系列的均值不超出历史均值范围为控制条件,经有限次试验确定预测值。结合嫩江流域尼尔基站控制断面以上1970年-2009年汛期(6月~9月)降雨资料,以1970年-2005年汛期降雨量为计算样本,预报2006年汛期降雨量,并以2006年实测降雨量进行检验,不断外推预测与检验,直至2010年。预测结果表明:当实际汛期降雨量属平水时,都会获得较高的预报精度,如2006年和2008年;在极枯情况,如2007年(降雨保证率为99.82%)的相对误差较大,为0.75;在较丰情况,如2009年(降雨保证率为19.63%)的相对误差也较大,为-0.20。所以,本方法适合平水年的预测,对于如何进行丰枯极值预报,最后从原理和方法上进行了探讨性思考。

英文摘要:

Based on Monte Carlo theory, this paper uses P-Ⅲ type distribution tuncnon to summarize me probability cnaracteristics of basin precipitation in flood season Under the control condition that the average of the sample series which includes the predicted values does not exceed the historical average range, the predictive values are determined after limited times tests. Com- bined with the flood season (from June to September) rainfall data from 1970 to 2009 up the control section of Nierji station in Nenjiang River Valley, and with the flood season rainfall data from 1970 to 2005 as the calculation sample, flood season rainfall in 2006 is then forecast. After the forecasting, the actual measured rainfall in 2006 is used to test this prediction, and then the extrapolating predictions and tests are continuously undertaken till 2010. The predicted results indicate that the prediction is of high accuracy with the actual rainfall in flood season in normal year, such as in the year of 2006 and 2008;in extremely dry con- ditions, the relative error is big, for example,in 2007, when the rainfall assurance is 99.82%,the error is as big as 0.75;in relatively water-abundant circumstances,the relative error is also big, such as in 2009, when the rainfall assurance is 19. 63%, the error is as large as -0. 20. So,this method is suitable for the flat water forecasting. This paper finally discussed how to forecast the extremums of abundant and dry years from the viewpint of theory and method.

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