Analysis of Trends in Low-Flow Time Series of Canadian Rivers

  • Deepesh Machiwal
  • Madan Kumar Jha


The main objective of studies on analysis of trends is to ascertain how the statistical characteristics (e.g., mean and variance) of hydrological variables change over time at a given location or at a number of locations in a watershed/ region. From the historical perspective, much of the earlier studies on temporal trends in time series of hydrological variables were focussed on water quality related parameters. Most of the earlier studies, reported during 1970s and 1980s, have been reviewed and documented in the work of Helsel and Hirsch (1992) and Hipel and McLeod (1994). Quite recently, interest in the investigation of trends in time series of hydrological variables has increased enormously and numerous studies have been undertaken in different parts of the world. It is difficult to present an exhaustive account of these studies in this chapter and therefore only some of these studies are listed here: Chiew and McMahon (1993), Yulianti and Burn (1998), Lins and Slack (1999), Douglas et al. (2000), Yue et al. (2002b), Robson (2002), Xiong and Shenglian (2004), Hannaford and Marsh (2006), Dixon et al. (2006), Fu et al. (2007), Khaliq et al. (2008, 2009a, 2009b) and Khaliq and Gachon (2010) for trends in streamflows (e.g. mean annual, low and high flows); Hisdal et al. (2001) for trends in hydrological droughts; Suppiah and Hennessy (1998), Haylock and Nicholls (2000), Kunkel et al. (2003), Krishnamurthy et al. (2009) and Kumar et al. (2010) for trends in precipitation related variables (e.g., annual or seasonal total precipitation, frequency and magnitude of extreme events and dry days). Scientific research on the identification of trends in time series of hydrological variables is still continuing, however using improved approaches and with an enhanced focus on the interpretation of trends. It is important to note that the majority of the studies on trends over the last two decades were driven mainly by concerns of climate change and less due to the influence of other factors like agricultural and industrial developments that could also influence time evolution of hydrological variables.


Generalize Extreme Value Hurst Exponent Hydrometric Station Nominal Significance Level Detrended Fluctuation Analysis Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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The authors are thankful to Prof. Madan Kumar Jha of Indian Institute of Technology Kharagpur and Dr. Deepesh Machiwal of Central Arid Zone Research Institute, India for their constructive comments and suggestions that led to an improved chapter


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Copyright information

© Capital Publishing Company 2012

Authors and Affiliations

  • Deepesh Machiwal
    • 1
  • Madan Kumar Jha
    • 2
  1. 1.Central Arid Zone Research Institute Regional Research StationGujaratIndia
  2. 2.Indian Institute of Technology KharagpurWest BengalIndia

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