Long-Term Trends and Variability of Hydroclimate Variables and Their Linkages with Climate Indices in the Songhua River

被引:3
作者
Ma, Chongya [1 ]
Pei, Wenhan [1 ]
Liu, Jiping [1 ]
Fu, Guobin [2 ]
机构
[1] Jilin Normal Univ, Coll Geog Sci & Tourism, Siping 136000, Peoples R China
[2] CSIRO Environm, Perth, WA 6014, Australia
关键词
climate indices; precipitation; Songhua River; streamflow; trend; variability; BASIN; STREAMFLOW; PRECIPITATION; OSCILLATION; IMPACTS; CHINA;
D O I
10.3390/atmos15020174
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The long-term trends and variability of hydroclimate variables are critical for water resource management, as well as adaptation to climate change. Three popular methods were used in this study to explore the trends and variability of hydroclimate variables during last 122 years in the Songhua River (SHR), one of most important river systems in China. Results show the followings: (1) There was an obvious pattern of decadal oscillations, with three positive and three negative precipitation and streamflow anomalies. The lengths of these phases vary from 11 to 36 years. (2) Annual temperature demonstrated a statistically significant increasing trend in the last 122 years, and the trend magnitude was 0.30 degrees C/10 years in the last 50-60 years, being larger than that of the global surface temperature. It has increased much faster since 1970. (3) Monthly precipitation in the winter season in recent years was almost the same as that in earlier periods, but a significantly increasing monthly streamflow was observed due to snowmelt under a warming climate. (4) A statistically significant correlation between hydroclimate variables and climate indices can be determined. These results could be used to make better water resource management decisions in the SHR, especially under future climate change scenarios.
引用
收藏
页数:18
相关论文
共 33 条
[1]   Complexity and trends analysis of hydrometeorological time series for a river streamflow: A case study of Songhua River Basin, China [J].
Faiz, M. A. ;
Liu, D. ;
Fu, Q. ;
Qamar, M. U. ;
Dong, S. ;
Khan, M. I. ;
Li, T. .
RIVER RESEARCH AND APPLICATIONS, 2018, 34 (02) :101-111
[2]   Hydro-climatic trends of the Yellow River basin for the last 50 years [J].
Fu, GB ;
Chen, SL ;
Liu, CM ;
Shepard, D .
CLIMATIC CHANGE, 2004, 65 (1-2) :149-178
[3]   Trends in Groundwater Levels in Alluvial Aquifers of the Murray-Darling Basin and Their Attributions [J].
Fu, Guobin ;
Rojas, Rodrigo ;
Gonzalez, Dennis .
WATER, 2022, 14 (11)
[4]   A two-parameter climate elasticity of streamflow index to assess climate change effects on annual streamflow [J].
Fu, Guobin ;
Charles, Stephen P. ;
Chiew, Francis H. S. .
WATER RESOURCES RESEARCH, 2007, 43 (11)
[5]   Updated high-resolution grids of monthly climatic observations - the CRU TS3.10 Dataset [J].
Harris, I. ;
Jones, P. D. ;
Osborn, T. J. ;
Lister, D. H. .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2014, 34 (03) :623-642
[6]   Version 4 of the CRU TS monthly high-resolution gridded multivariate climate dataset [J].
Harris, Ian ;
Osborn, Timothy J. ;
Jones, Phil ;
Lister, David .
SCIENTIFIC DATA, 2020, 7 (01)
[7]   A Tripole Index for the Interdecadal Pacific Oscillation [J].
Henley, Benjamin J. ;
Gergis, Joelle ;
Karoly, David J. ;
Power, Scott ;
Kennedy, John ;
Folland, Chris K. .
CLIMATE DYNAMICS, 2015, 45 (11-12) :3077-3090
[8]   TECHNIQUES OF TREND ANALYSIS FOR MONTHLY WATER-QUALITY DATA [J].
HIRSCH, RM ;
SLACK, JR ;
SMITH, RA .
WATER RESOURCES RESEARCH, 1982, 18 (01) :107-121
[9]  
Kendall M. G., 1948, Rank correlation methods.
[10]   Precipitation variability assessment of northeast China: Songhua River basin [J].
Khan, Muhammad Imran ;
Liu, Dong ;
Fu, Qiang ;
Azmat, Muhammad ;
Luo, Mingjie ;
Hu, Yuxiang ;
Zhang, Yongjia ;
Abrar, Faiz M. .
JOURNAL OF EARTH SYSTEM SCIENCE, 2016, 125 (05) :957-968