孙军艳, 刘禹, 蔡秋芳, 包光, 孙铂, 宋慧明. 以树木年轮资料重建黄河上游大通河480年以来6—7月径流变化历史[J]. 海洋地质与第四纪地质, 2011, 31(3): 109-116. DOI: 10.3724/SP.J.1140.2011.03109
引用本文: 孙军艳, 刘禹, 蔡秋芳, 包光, 孙铂, 宋慧明. 以树木年轮资料重建黄河上游大通河480年以来6—7月径流变化历史[J]. 海洋地质与第四纪地质, 2011, 31(3): 109-116. DOI: 10.3724/SP.J.1140.2011.03109
SUN Junyan, LIU Yu, CAI Qiufang, BAO Guang, SUN Bo, SONG Huiming. TREE-RING BASED JUNE-JULY RUNOFF RECONSTRUCTION FOR THE DATONG RIVER WATERSHED, WESTERN CHINA SINCE AD1525[J]. Marine Geology & Quaternary Geology, 2011, 31(3): 109-116. DOI: 10.3724/SP.J.1140.2011.03109
Citation: SUN Junyan, LIU Yu, CAI Qiufang, BAO Guang, SUN Bo, SONG Huiming. TREE-RING BASED JUNE-JULY RUNOFF RECONSTRUCTION FOR THE DATONG RIVER WATERSHED, WESTERN CHINA SINCE AD1525[J]. Marine Geology & Quaternary Geology, 2011, 31(3): 109-116. DOI: 10.3724/SP.J.1140.2011.03109

以树木年轮资料重建黄河上游大通河480年以来6—7月径流变化历史

TREE-RING BASED JUNE-JULY RUNOFF RECONSTRUCTION FOR THE DATONG RIVER WATERSHED, WESTERN CHINA SINCE AD1525

  • 摘要: 通过分析祁连山地区的3组祁连圆柏树木年轮样本,发现大通河河水补给区祁连山地区的祁连圆柏树轮资料与大通河6-7月径流量显著相关,在此基础上设计转换方程,重建了大通河1525-2009年以来6-7月径流变化历史,重建的径流变化序列中存在5个丰水期:1530-1555、1576-1586、1733-1760、1776-1786、1855-1912和5个枯水期:1670-1680、1691-1730、1814-1836、1926-1942、1964-1978年,在径流偏少的枯水时段,径流量的标准差较大,在径流偏多的丰水时段,径流量的标准差较小;另外,在径流偏少较多的时段以及在径流偏多较多的时段,其标准差σ都比较大,表明在旱或涝较严重的时段,其径流的年际变化均较大。功率谱分析发现重建的近450年来大通河6-7月径流存在准2 a (2.04~2.3)、准50 a (50~57)、100 a、133 a和200 a的周期。

     

    Abstract: A tree-ring chronology has been built up based on the tree-ring samples from the Qilian Mountains. Response analysis showed that there is significant relationship between the tree-ring width and the June to July runoff of the Datong River watershed. Based on the analysis, a transfer function was designed to reconstruct the total runoff from June to July of the Datong River during the period 1525-2009. There are 5 wet and 5 dry periods in the reconstructed runoff history. The wet periods are 1530-1555,1576-1586,1733-1760,1776-1786,1855-1912, and the dry periods 670-1680,1691-1730,1814-1836,1926-1942,1964-1978 respetively. The reconstructed series also displayed that the standard deviations in the dry periods are higher than the wet periods, and the extreme dry and wet periods have the highest standard deviation. The reconstructed June-July runoff series shows significant periodicities around 2 (2.04~2.3),50 (50~57),100, 133 and 200years.

     

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