Spatial Variation and Trends in PDSI and SPI Indices and Their Relation to Streamflow in 10 Large Regions of China
Spatial Variation and Trends in PDSI and SPI Indices and Their Relation to Streamflow in 10 Large Regions of China
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中国10个大区PDSI和SPI指数的空间变化、趋势及其与径流的关系
DOI：
10.1175/2009jcli2968.1
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发表时间：
2010-02
影响因子：
4.9
通讯作者：
Krysanova, Valentina
中科院分区：
文献类型：
--
作者：
Zhai, Jianqing;Vetter, Tobias;Jiang, Tong;Gao, Chao;Su, Buda;Krysanova, Valentina
Time series of the average annual Palmer drought severity index (PDSI) and standardized precipitation index (SPI) were calculated for 483 meteorological stations in China using monthly data from 1961 to 2005. The time series were analyzed for 10 large regions covering the territory of China and represented by seven river basins and three areas in the southeast, southwest, and northwest. Results show that the frequencies of both dry and wet years for the whole period are lower for southern basins than for the northern ones when estimated by PDSI but very similar for all basins when calculated by SPI. The frequencies of dry and wet years calculated for 5- and 15-yr subperiods by both indices show the upward dry trends for three northeastern basins, Songhuajiang, Liaohe, and Haihe; a downward dry trend for the northwest region; a downward wet trend for the Yellow River basin; and an upward wet trend for the northwest region. Trend detection using PDSI indicates statistically significant negative trends for many stations in the northeastern basins (Songhuajiang, Liaohe, Haihe, and Yellow) and in the middle part of the Yangtze, whereas statistically significant positive trends were found in the mountainous part of the northwest region and for some stations in the upper and lower Yangtze. A moderately high and statistically significant correlation between the percentage of runoff anomaly (PRA) and the annual average PDSI and SPI was found for six large rivers. The results confirm that PDSI and SPI indices can be used to describe the tendency of dryness and wetness severity and for comparison in climate impact assessment.
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影响因子：
6.7
作者：
T. Mckee;N. Doesken;J. Kleist
通讯作者：
T. Mckee;N. Doesken;J. Kleist
DOI：
--
发表时间：
2007
期刊：
Arid Land Geography
影响因子：
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作者：
Yang Lan-fang
通讯作者：
Yang Lan-fang
DOI：
--
发表时间：
2003
期刊：
--
影响因子：
--
作者：
W. Jie;S. Regional
通讯作者：
W. Jie;S. Regional
DOI：
--
发表时间：
2003
期刊：
--
影响因子：
--
作者：
W. Jie
通讯作者：
W. Jie
影响因子：
4.9
作者：
M. Ting;M. Hoerling;Taiyi Xu;Arun Kumar
通讯作者：
M. Ting;M. Hoerling;Taiyi Xu;Arun Kumar