To prewhiten or not to prewhiten in trend analysis?

Bayazit, M.; Önöz, Bihrat

doi:10.1623/hysj.52.4.611

Cited by 284 publications

(169 citation statements)

References 18 publications

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“…A serious problem in detecting and evaluating trends in hydrological data is the effect of serial dependence [61][62][63][64][65][66][67]. If an autocorrelation exists in a time series, the MK test tends to reject the null According to the Slovak Hydrometeorological Institute (SHMI), average annual rainfalls of less than 600 mm may occur in Slovakia.…”

Section: Resultsmentioning

confidence: 99%

“…It is also widely used in environmental science because it is simple, robust, and can cope with missing values and values below a detection limit. A serious problem in detecting and evaluating trends in hydrological data is the effect of serial dependence [61][62][63][64][65][66][67]. If an autocorrelation exists in a time series, the MK test tends to reject the null hypothesis of no trend more often than the specified level of significance [68].…”

Section: Resultsmentioning

confidence: 99%

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Precipitation Trends over Slovakia in the Period 1981–2013

Zeleňáková

Vido

Portela

et al. 2017

Water

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Abstract:The objective of this paper was to analyze the temporal and spatial trends in annual and seasonal precipitation in Slovakia utilizing 487 gauging station data collected statewide in the period from 1981 to 2013. The nonparametric Mann-Kendall (MK) statistical test, which has been widely used to assess the significance of trends in hydrological time series, was applied to detect the significant trends. The Theil-Sen (TS) approach was applied to quantify the trend magnitude, and the Sequential Mann-Kendall (SQMK) test was used to detect abrupt temporal trend shifts. In general, precipitation data in the study area have not changed during the last 33 years, and there are no big gaps. However, predominantly increasing trends in precipitation time series were found at most of the gauging stations in Slovakia. The results corroborate previous climatic studies in the area of central Europe. In Slovakia, there is evidence of different rain distribution from the monthly point of view. Decreasing trends were detected in December in the northern part of Slovakia, while the central and southern parts revealed increasing trends. Most of the stations showed increasing summer precipitation trends, especially in July. It is expected that the findings of this comprehensive study of precipitation trends over Slovakia will produce more insights for the understanding of the regional hydrological behavior in Slovakia over the last several decades.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Precipitation Trends over Slovakia in the Period 1981–2013

Zeleňáková

Vido

Portela

et al. 2017

Water

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“…Therefore, it is essential to remove autocorrelation from data before using them in MK and SR tests for detection of trends. Von Storch (1995) proposed a method named prewhitening to remove undesired influence of data dependence (Bayazit and Onoz 2007).…”

Section: Trend Testsmentioning

confidence: 99%

Extreme Rainfall Nonstationarity Investigation and Intensity–Frequency–Duration Relationship

2014

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Non-stationary behaviour of recent climate increases concerns amongst hydrologists about the currently used design rainfall estimates. Therefore, it is necessary to perform analysis to confirm stationarity or detect non-stationarity of extreme rainfall data in order to derive accurate design rainfall estimates for infrastructure projects and flood mitigation works.Extreme rainfall non-stationarity analysis of the storm durations from 6 min to 72 hours was conducted in this study using data from the Melbourne Regional Office station in Melbourne (Australia) for the period of 1925-2010. Stationary Generalized Extreme Value (GEV) models were constructed to obtain Intensity-Frequency-Duration relationships for the above storm durations using data of two time periods : 1925-1966 and 1967-2010 after identifying the year 1967 as the change point year. Design rainfall estimates of the stationary models for the two periods were compared to identify the possible changes. Non-stationary GEV models, which were developed for storm durations that showed statistically significant extreme rainfall trends, did not show advantage over stationary GEV models. There was no evidence of non-stationarity according to stationarity tests, despite the presence of statistically significant extreme rainfall trends. The developed methodology consisting of trend and nonstationarity tests, change point analysis, and stationary and non-stationary GEV models was demonstrated successfully using the data of the selected station.

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“…It is well known that the M-K test, devised for independent data, rejects the null hypothesis of no trend more often than specified by the significance level applied to autocorrelated series [82][83][84]. Therefore, prewhitening should be applied to autocorrelated series before performing the M-K test to eliminate the influence of serial autocorrelation on the trend detection of data series [84].…”

Section: Methods Of Trend Analysismentioning

confidence: 99%

“…Therefore, prewhitening should be applied to autocorrelated series before performing the M-K test to eliminate the influence of serial autocorrelation on the trend detection of data series [84]. This study used the M-K test to detect possible trends in the summer NAOI series, the annual and seasonal SPI/SPEI series, and all drought station proportion series in Ningxia, during years 1972-2011.…”

Section: Methods Of Trend Analysismentioning

confidence: 99%

Temporal-Spatial Variation of Drought Indicated by SPI and SPEI in Ningxia Hui Autonomous Region, China

2015

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Abstract:The Ningxia Hui Autonomous Region of China (Ningxia) is an important food production area in northwest China severely affected by drought. The Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were calculated based on monthly meteorological data to explore climate change and variation in drought intensity, duration, frequency, and spatial extent in Ningxia during 1972-2011 show that the SPEI is more applicable than the SPI for exploring climate change and drought variation in Ningxia. The Ningxia climate experienced a significant drying tendency. Annual SPEI decreased about 0.37 decade −1 during 1972-2011. Drought was exacerbated by this drying tendency. Regional average duration, maximum duration, intensity, and frequency of drought identified by the SPEI increased by one month, three months, 0.15%, and 36.1%, respectively, during 1992-2011 compared to the period of 1972-1991. The spatial extent of drought identified by the SPEI increased about 14.4% decade −1 in the spring during 1972-2011. Spatially, drought frequency increased from north to south. Average intensity (maximum duration) of drought calculated by the SPEI increased (decreased) northward and southward from the central arid area.

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To prewhiten or not to prewhiten in trend analysis?

Cited by 284 publications

References 18 publications

Precipitation Trends over Slovakia in the Period 1981–2013

Precipitation Trends over Slovakia in the Period 1981–2013

Extreme Rainfall Nonstationarity Investigation and Intensity–Frequency–Duration Relationship

Temporal-Spatial Variation of Drought Indicated by SPI and SPEI in Ningxia Hui Autonomous Region, China

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