Geoscience Reference
In-Depth Information
8
Trend and Homogeneity in
Subsurface Hydrologic Variables:
Case Study in a Hard-Rock
Aquifer of Western India
8.1 Introduction
A comprehensive review on the applications of time series analysis in surface
water hydrology, climatology and groundwater hydrology (Machiwal and
Jha, 2006) revealed that although several studies deal with the application of
time series analysis in surface water hydrology, the application of time series
analysis in subsurface hydrology is greatly limited. In subsurface hydrology,
time series analysis has been mostly used for detecting trends in groundwater
quality (Loftis, 1996; Broers and van der Grift, 2004; Chang, 2008; Visser et
al., 2009).
Trend and homogeneity are the two most important characteristics of
hydrologic time series, which have been investigated in most studies (e.g.,
Esterby, 1996; Loftis, 1996; Hess et al., 2001; Machiwal and Jha, 2006). A
time series is said to have trends, if there is a significant correlation (positive
or negative) between the observations and time. Trends and shifts in hydrologic
time series are usually introduced due to natural or artificial changes (Salas,
1993). The trend in a time series can be expressed by a suitable linear or
nonlinear model. However, the linear models are more widely used in hydrology
than the nonlinear ones (Shahin et al., 1993). Various parametric and
nonparametric statistical tests have been reported in the literature for detecting
the trend in the hydrologic time series, viz., turning point test, the Kendall's
phase test, the Kendall's rank correlation test, regression test, the Wald-
Wolfowitz total number of runs test, sum of squared lengths test, adjacency
test, difference sign test, the run test on successive differences, inversion test
(Shahin et al., 1993), the Spearman rank order correlation test, the Mann-
 
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