The influence of nonlinear trends on the power of the trend-free pre-whitening approach

dc.creatorGabriel Constantino Blain
dc.date2015
dc.date.accessioned2026-07-07T03:53:48Z
dc.descriptionThe Mann-Kendall test has been widely used to detect trends in agro-meteorological as well as hydrological time series. Trend-free pre-whitening (TFPW-MK) is an approach that improves the performance of this test in the presence of serial correlation. The main goal of this study was to evaluate the ability of TFPW-MK to detect nonlinear trends. As a case study, this approach was also applied to 10-day values of precipitation (P), potential evapotranspiration (PE) and the difference between P and PE (P- PE) obtained from the weather station of Ribeirão Preto, State of São Paulo, Brazil. The results obtained from Monte Carlo simulations indicate that upward convex trends increase the power of this test, while upward concave trends decrease its power. The results obtained from the location of Ribeirão Preto reveal an increasing pressure on agricultural water management due to growing PE values. Thus, we conclude that the power of the TFPW-MK is affected by the shape of the trend and that the hypothesis of the absence of climate change in the abovementioned location cannot be accepted.
dc.formatapplication/pdf
dc.identifier1679-9275
dc.identifierhttps://www.redalyc.org/articulo.oa?id=303033072003
dc.identifier.urihttp://hdl.handle.net/123456789/446542
dc.languageen
dc.publisherUniversidade Estadual de Maringá
dc.relationhttp://www.redalyc.org/revista.oa?id=3030
dc.rightsActa Scientiarum. Agronomy
dc.sourceActa Scientiarum. Agronomy (Brasil) Num.1 Vol.37
dc.subjectAgrociencias
dc.titleThe influence of nonlinear trends on the power of the trend-free pre-whitening approach
dc.typeartículo científico

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