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基于气候模式统计降尺度技术的未来青海湖水位变化预估
引用本文:刘吉峰,李世杰,丁裕国.基于气候模式统计降尺度技术的未来青海湖水位变化预估[J].水科学进展,2008,19(2):184-191.
作者姓名:刘吉峰  李世杰  丁裕国
作者单位:1.中国科学院南京地理与湖泊研究所, 江苏, 南京, 210008;
摘    要:借助于全球气候模式(德国MPI ECHAM5.0)输出信息和流域最近40年的气象观测资料,建立青海湖流域统计降尺度模式(QH-SDM),从而得到流域尺度未来30年(2010-2030年)气候变化情景,并由此驱动水文模型SWAT及湖泊水量平衡模型模拟了青海湖近几十年水位变化过程,预估了未来30年青海湖湖泊水文变化情景。结果表明,青海湖水位的未来变化将经历缓慢下降、逐渐回升、稳步升高3个阶段,到2030年,湖泊水位将达到3195.4 m左右,高出目前水位约2.2 m,面积接近4500 km2,蓄水量达到813亿m3,湖泊恢复到了20世纪70年代初的水平,预计这一结果将会缓解目前青海湖流域水资源紧缺的格局,并有利于植被恢复,减少土地沙化面积,对流域生态环境的改善和国民经济的发展将十分有益。

关 键 词:SWAT水文模型    统计降尺度    青海湖    水位变化    气候情景
文章编号:1001-6791(2008)02-0184-08
收稿时间:2007-06-21
修稿时间:2007年6月21日

Forecasting of water level of Qinghai lake on statistics downscaling from climatic model
LIU Ji-feng,LI Shi-jie,DING Yu-guo.Forecasting of water level of Qinghai lake on statistics downscaling from climatic model[J].Advances in Water Science,2008,19(2):184-191.
Authors:LIU Ji-feng  LI Shi-jie  DING Yu-guo
Affiliation:1.Nanjing Institute of Geography and Limnoloy, Chinese Academy of Sciences, Nanjing 210008, China;2.Hydrology Bureau, Yellow River Water Conservancy Committee of China, Zhengzhou 450004, China;3.Nanjing University of Information Science and Technology, Nanjing 210044, China
Abstract:The statistic downscaling models of Qinghai lake(QHSDM)are built in this paper by the output from AOGCM (Germany MPI ECHAM510)and local observed data in recent 40 years.The climate scenarios in the 30 years(2001-2030) are obtained and used to predict water-level changing of Qinghai lake in the same period.The results indicate that the water level changes of Qinghai lake would experience three phases:slowly descending,gradually ascending and steadily arising.In 2030,the lake level would rise to about 3195 14 m,about 212 m higher than present,the lake area will approach 4 500 km2 and the lake storage near 8.300 millions m3,Qinghai lake turn back to the status of 1970s in 20th century.It would alleviate the present water resources tension in the catchment of Qinghai lake,recover local vegetation and reduce the soil degenerating1 In short,it is beneficial to local ecology and social economics.
Keywords:
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