Graphical-statistical method to explore variability of hydrological time series

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dc.contributor.authorOnyutha, Charles
dc.date.accessioned2022-09-14T20:12:17Z
dc.date.available2022-09-14T20:12:17Z
dc.date.issued2021
dc.description.abstractDue 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.en_US
dc.identifier.citationOnyutha, C. (2021). Graphical-statistical method to explore variability of hydrological time series. Hydrology Research, 52(1), 266-283. doi: 10.2166/nh.2020.111en_US
dc.identifier.other10.2166/nh.2020.111
dc.identifier.urihttps://nru.uncst.go.ug/handle/123456789/4744
dc.language.isoenen_US
dc.publisherHydrology Researchen_US
dc.subjectClimate variabilityen_US
dc.subjectHydrological change attributionen_US
dc.subjectMann–Kendall testen_US
dc.subjectRiver Nileen_US
dc.subjectSpearman’s rho testen_US
dc.subjectSub-trend analysisen_US
dc.titleGraphical-statistical method to explore variability of hydrological time seriesen_US
dc.typeArticleen_US
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