TECHNIQUES OF TREND ANALYSIS FOR MONTHLY WATER-QUALITY DATA
TECHNIQUES OF TREND ANALYSIS FOR MONTHLY WATER-QUALITY DATA
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DOI:
10.1029/wr018i001p00107
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发表时间:
1982-01-01
影响因子:
5.4
通讯作者:
SMITH, RA
中科院分区:
文献类型:
--
作者:
HIRSCH, RM;SLACK, JR;SMITH, RA
Some characteristics that complicate the analysis of water quality time series are unnatural distributions, seasonality, flow relatedness, missing values, values below the limit of detection and serial correlation. Presented were techniques that were suitable in the face of the complications listed for the exploratory analysis of monthly water quality data for monotonic trends. The 1st procedure, the seasonal Kendall test, was a nonparametric test for trend applicable to data sets with seasonality, missing values or values reported as less than. Under realistic stochastic processes (exhibiting seasonality, skewness and serial correlation), it was robust in comparison to parametric alternatives, although the seasonal Kendall test or the alternatives can not be considered an exact test in the presence of serial correlation. The 2nd procedure, the seasonal Kendall slope estimator, was an estimator of trend magnitude. It was an unbiased estimator of the slope of a linear trend and had higher precision than a regression estimator where data were highly skewed but somewhat lower precision where the data were normal. The 3rd procedure provided a means for testing for change over time in the relationship between constituent concentration and flow, avoiding the probem of identifying trends in water quality that were artifacts of the particular sequence of discharges observed (e.g., drought effects). In this method a flow-adjusted concentration was defined as the residual (actual minus conditional expectation) based on a regression of concentration on some function of discharge. These flow-adjusted concentrations, which may also be seasonal and unnatural, could be tested for trend by using the seasonal Kendall test.