Regional streamflow trend detection with consideration of both temporal and spatial correlation

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Abstract

It is known that serial correlation within time series at sites and cross-correlation among sites in a specific region will influence the ability of statistical tests to assess the field significance of trends over the region. However, serial and/or cross-correlation has been ignored in field trend-analyses. This study attempts to develop a methodology that takes into account both serial and cross-correlation in the assessment of the field significance of trends. The regional average Mann–Kendall (RAMK) statistic is used to represent the regional properties of trends at a regional scale. The null distribution of the RAMK statistic is derived on the basis that the joint probability distribution of m independent normal variables is also normally distributed. The variance of the RAMK statistic is then modified by serial and cross-correlation. The applicability of the method was demonstrated by applying it to assess the field significance of trends in annual mean, annual maximum, and annual minimum daily streamflow from 1967 to 1996 in ten major homogeneous climate regions of Canada. The results indicate that the method developed provides more accurate assessment of the field significance of trends than that without consideration of serial and cross-correlation.

At the significance level of 0.10, annual mean daily flow increased significantly in the region of Yukon and northern BC mountains whereas it decreased significantly in the Pacific and the Prairie regions. Annual maximum daily flow decreased significantly across southern Canada, except in the Pacific region. Annual minimum daily flow decreased significantly in the Pacific region and in southeastern Canada, with the exception of the region of Great Lakes and St Lawrence river basin, whereas it increased significantly in the region of Yukon and northern BC mountains. Copyright © 2002 Royal Meteorological Society

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