Graphical-statistical method to explore variability of hydrological time series
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Date
2021
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Hydrology Research
Abstract
Due to increasing concern on developing measures for predictive adaptation to climate change
impacts on hydrology, several studies have tended to be conducted on trends in climatic data.
Conventionally, trend analysis comprises testing the null hypothesis H0 (no trend) by applying the
Mann–Kendall or Spearman’s rho test to the entire time series. This leads to lack of information about
hidden short-durational increasing or decreasing trends (hereinafter called sub-trends) in the data.
Furthermore, common trend tests are purely statistical in nature and their results can be meaningless
sometimes, especially when not supported by graphical exploration of changes in the data. This paper
presents a graphical-statistical methodology to identify and separately analyze sub-trends for
supporting attribution of hydrological changes. The method is based on cumulative sum of differences
between exceedance and non-exceedance counts of data points. Through the method, it is possible to
appreciate that climate variability comprises large-scale random fluctuations in terms of rising and
falling hydro-climatic sub-trends which can be associated with certain attributes. Illustration on how to
apply the introduced methodology was made using data over the White Nile region in Africa. Links for
downloading a tool called CSD-VAT to implement the presented methodology were provided.
Description
Keywords
Climate variability, Hydrological change attribution, Mann–Kendall test, River Nile, Spearman’s rho test, Sub-trend analysis
Citation
Onyutha, C. (2021). Graphical-statistical method to explore variability of hydrological time series. Hydrology Research, 52(1), 266-283. doi: 10.2166/nh.2020.111