Hydrology and Water Resources

Changing properties of low streamflow: Possible causes and implications

Expand
  • Department of Water Resources and Environment, Sun Yat-sen University, Guangzhou 510275, China; Key Laboratory of Water Cycle and Water Security in Southern China, Guangdong High Education Institute, Sun Yat-sen University, Guangzhou 510275, China

Received date: 2010-11-21

  Revised date: 2011-04-12

  Online published: 2011-09-20

Abstract

In this study, 11 probability distribution functions are adopted to systematically analyze the probability behaviors of the 7-day low flow regimes (the minimum average flow for the consecutive 7 days) at six hydrological stations located in the "Five Rivers" in the Poyang Lake Basin. The L-moment technique is used to estimate the parameters of the probability functions and the Kolmogorov-Smirnov method (K-S) is accepted to evaluate the goodness-of-fit of the probability functions. Trends within the 7-day low flow series are tested using the Mann-Kendall (M-K) method. The results show that: (1) Wake distribution is the candidate distribution function with the highest goodness-of-fit in the study of the extreme flow regimes over the Poyang Lake basin; (2) The 7-day low flow is in significant decrease at Lijiadu station. The frequency of the 7-day low flow regimes tends to increase after the 1970s; The 7-day low flow at the other five stations is in an increasing trend and the probability of dry episodes is decreasing. The 7-day low flow at Hushan and Wanjiabu stations is in significant increase in the mid-1980s; Moreover, variability of the 7-day low flow at Waizhou station is the smallest, and that at Lijiadu station is the largest; (3) Precipitation changes are one of the major factors influencing the 7-day low flow changes. Hydraulic facilities are helpful to the decrease of the streamflow magnitude. Besides, forestation can flatten the variability of the 7-day low flow changes. The results of this study could be of scientific and practical merits in terms of good understanding of extreme flow changes under the influences of climate changes and human activities.

Cite this article

SUN Peng, ZHANG Qiang, CHEN Xiao-hong . Changing properties of low streamflow: Possible causes and implications[J]. GEOGRAPHICAL RESEARCH, 2011 , 30(9) : 1702 -1712 . DOI: 10.11821/yj2011090014

References

[1] Milly P C D, Wetherald P T. Increasing risk of great floods in a changing climate. Nature, 2002, 415(6871): 514~517.

[2] Palmer T N, J Räisänen. Quantifying the risk of extreme seasonal precipitation events in a changing climate. Nature, 2002, 415: 512~514.

[3] Easterling D E, Meehl A G, Parmesan C, et al. Climate extremes: Observations, modeling, and impacts. Science, 2000, 689: 2068~2074.

[4] Zhang Qiang, Marco Gemmer, Chen Jiaqi. Climate changes and flood/drought variation and flood risk in the Yangtze Delta, China. Quaternary International, 2008: 62~69.

[5] Beniston M, Stephenson D B. Extreme climatic events and their evolution under changing climatic conditions. Global and Planetary Change, 2004, 44: 1~9.

[6] Zhang Qiang, Liu Chun ling, Xu Chong-yu. Observed trends of annual maximum water level and streamflow during past 130 years in the Yangtze River basin, China. Journal of Hydrology, 2006, 324: 255~265.

[7] 谢军, 黄智权, 杨巧言. 江西省自然地理志. 北京: 方志出版社, 2003. 213~219.

[8] 李世勤, 闵骞, 谭国良, 等. 鄱阳湖2006年枯水特征及其成因研究. 水文,2008, 28(6): 73~76.

[9] 郭华, 姜彤. 鄱阳湖流域洪峰流量和枯水流量变化趋势分析. 自然灾害学报, 2008, 17(3): 75~80.

[10] 郭华, 姜彤, 王国杰, 等. 1961~2003年间鄱阳湖流域气候变化趋势及突变分析. 湖泊科学, 2006, 18(5): 443~451.

[11] 闵骞. 鄱阳湖区干旱与变化. 江西水利科技, 2006, 9: 125~128.

[12] Svensson C, Kundzewicz Z W, Maurer T. Trend detection in river flow series:2.Flood and low-flow index series. Hydrological Sciences-Journal, 2005, 50(5): 811~824.

[13] David R M. Handbook of Hydrology. New York: McGraw-Hill Professional Publishing, 1993.

[14] Ana Justel, Daniel Pefia, Rubrn Zamar. A multivariate Kolmogorov-Smimov test of goodness of fit. Statistics & Probability Letters, 1997, 35: 251~259.

[15] Hosking J R M. L-moments: Analysis and estimation of distributions using linear combinations of order statistics. Journal of the Royal Statistical Society: Series B, 1990, 52: 105~124.

[16] Von Storch, V.H. Misuses of statistical analysis in climate research. In: Storch H V, Navarra A. Analysis of climate variability: Application of statistical techniques. Berlin: Springer-Verlag, 1995. 11~26.

[17] Sanjiv Kumar, Venkatesh Merwade. Streamflow trends in Indiana: Effects of long term persistence, precipitation and subsurface drains. Journal of Hydrology, 374: 171~183.

[18] Kulkarni A, H von Stroch. Monte Carlo experiments on the effect of serial correlation on the Mann-Kendall test of trend. Meteorologische Zeitschrift, 1995, 4(2): 82~85.

[19] Zhang Qiang, Xu Chong-Yu, Zhang Zengxin, et al. Spatial and temporal variability of precipitation maxima during 1960~2005 in the Yangtze River basin and possible association with large-scale circulation. Journal of Hydrology, 2008, 353: 215~227.

[20] 王英, 曹明奎, 陶波. 全球气候变化背景下中国降水量空间格局的变化特征. 地理研究, 2006, 25(6): 1031~1040.

[21] 张天宇, 程炳岩, 刘晓冉. 近45年长江中下游地区汛期极端强降水事件分析. 气象, 2007, 33(10): 80~87.

[22] 高歌, 陈德亮, 任国玉, 等. 1956~2000年中国潜在蒸散量变化趋势. 地理研究, 2006, 25(3): 378~387.

[23] 江西文明信息库. http://ziliaoku.jxwmw.cn/huanpoyanghu/pohuliuyu/, 2008-11.

[24] 许炯心. 长江上游干支流的水沙变化及其与森林破坏的关系. 水利学报, 2000, 1: 72~80.
Outlines

/