4.7 Article

Temporal evolution of low-flow regimes in Canadian rivers

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WATER RESOURCES RESEARCH
卷 44, 期 8, 页码 -

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AMER GEOPHYSICAL UNION
DOI: 10.1029/2007WR006132

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  1. Ouranos Consortium on Regional Climatology
  2. Adaptation to Climate Change, National Science and Engineering Research Council (NSERC) of Canada
  3. Environment Canada (Adaptation and Impacts Research Division)

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This study investigates temporal evolution of 1-, 7-, 15-, and 30-day annual and seasonal low-flow regimes of pristine river basins, included in the Canadian reference hydrometric basin network (RHBN), for three time frames: 1974-2003, 1964-2003, and 1954-2003. For the analysis, the RHBN stations are classified into three categories, which correspond to stations where annual low flows occur in winter only, summer only, and both summer and winter seasons, respectively. Unlike in previous studies for the RHBN, such classification is essential to better understand and interpret the identified trends in low-flow regimes in the RHBN. Nonparametric trend detection and bootstrap resampling approaches are used for the assessment of at-site temporal trends under the assumption of no persistence or short-term persistence (STP). The results of the study demonstrate that previously suggested prewhitening and trend-free prewhitening approaches, for incorporating the effect of STP on trend significance, are not adequate for reliably identifying trends in low-flow regimes compared to a simple bootstrap-based approach. The analyses of 10 relatively longer records reveal that trends in low-flow regimes exhibit fluctuating behavior, and hence, their temporal and spatial interpretations appear to be sensitive to the time frame chosen for the analysis. Furthermore, under the assumption of long-term persistence (LTP), which is a possible explanation for the fluctuating behavior of trends, many of the significant trends in low-flow regimes, noted under the assumption of STP, become nonsignificant and their field significance also disappears. Therefore correct identification of STP or LTP in time series of low-flow regimes is very important as it has serious implications for the detection and interpretation of trends.

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