The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series

Yue, Sheng; Wang, ChunYuan

doi:10.1023/b:warm.0000043140.61082.60

Cited by 1,070 publications

(704 citation statements)

References 30 publications

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“…This is because they are not only simple to use, but they are also resilient to skewed distribution, missing values and values that fall outside the detection limit, and to the nonstationary nature of data (Chaouche et al 2010;Jeneiova et al 2014). However, the MK test does not account for the serial correlation that very often exists in hydrological time series (Yue and Wang 2004;Partal and Küçük 2006). The presence of serial correlation in a data set may lead to a misleading interpretation because it enhances the probability of finding a significant trend, when actually there is an absence of such a trend.…”

Section: Trend Detection Methods Applied In the Studymentioning

confidence: 99%

“…The rejection of the null hypothesis (understood here as ''no trend'') will be more likely to occur when in fact it should be accepted (Hamed and Rao 1998;Partal 2010). Positive serial correlation can lead to an increase in falsely rejecting the null hypothesis (Douglas et al 2000), whereas the presence of a negative serial correlation can lead to an increase in falsely accepting the null hypothesis (Yue and Wang 2004). As such, it is important to address the issue of serial correlation in time series prior to applying a trend test.…”

Section: Introductionmentioning

confidence: 98%

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Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

2017

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The aim of the study is to investigate trends in selected hydroclimatic indices using novel and conventional tools, for future climate projections in the twentyfirst century. Selected quasi-natural Norwegian and Polish catchments are used as a case study. The projected flows are provided by GR4J rainfall-runoff conceptual model, coupled with an ensemble of climate model projections from EURO-CORDEX initiative. The trends are analysed using conventional Mann-Kendall and modified MannKendall statistical approaches, a time-frequency approach based on discrete wavelet transform (DWT) and the dynamic harmonic regression (DHR) method. Of all methods applied the DHR gives the most conservative trend estimates. Trends depend on the specific hydroclimatic character and flow regime of the catchment. The results confirmed that in catchments with a rainfall-driven flood regime, an increase in the amount of precipitation is followed by increased flows, with strong seasonal changes, whereas, in catchments with a snow-driven flood regime, despite an increase of mean annual flow, decrease in annual maximum flow is observed. Generally, positive trend is the most dominant in all catchments studied and the methods were consistent in detection of trend except in seasonal trend test.

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Section: Trend Detection Methods Applied In the Studymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 98%

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

2017

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“…Before performing these analyses, whether the lag-1 correlation is significantly different from 0 at the 5% level is checked. The presence of autocorrelation can affect the significance of the trend tests (Kulkarni and von Storch, 1995;Yue et al, 2003;Yue and Wang, 2004;Hamed, 2009), resulting in the detection of statistically significant trends even though no trend is present (Cox and Stuart, 1955;Cohn and Lins, 2005). Out of 27 stations, only one has a lag-1 value slightly outside of the 95% confidence intervals.…”

Section: Stationaritymentioning

confidence: 99%

Analyses of extreme flooding in Austria over the period 1951–2006

Villarini

Smith

Serinaldi

et al. 2011

Intl Journal of Climatology

102

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ABSTRACT:Analyses of extreme flooding in Austria is performed using daily discharge time series from 27 stations over the period . The main research questions revolve around: (1) temporal non-stationarities in the flood record, (2) upper tail and scaling properties of the flood peak records, and (3) relation between magnitude and frequency of flooding and the North Atlantic Oscillation (NAO). Two datasets are derived from the daily discharge time series: annual maximum daily discharge and peaks-over-threshold (POT) data. The validity of the stationarity assumption in the annual maximum discharge record is assessed by investigating the presence of abrupt and slowly varying changes using nonparametric tests. The time series are tested for abrupt changes both in the mean and variance of the flood peak distributions by means of the Pettitt test. The presence of monotonic trends is investigated by means of the Mann-Kendall and Spearman tests. Violations of the stationarity assumption are associated with abrupt rather than gradual changes. These step changes generally involve river regulation through construction of dams or other major engineering works. It is not possible to make conclusive statements about the presence of an anthropogenic climate change signal in the flood peak record. Similar conclusions are obtained when focussing on the frequency of POT floods. The Generalised Extreme Value distribution is used to study the upper tail and scaling properties of annual maximum daily discharge records. The location and scale parameters exhibit power-law behaviour as a function of drainage area. The shape parameters indicate that the flood peak distributions for Austria have a heavy tail. Non-stationary modelling of the annual maximum daily discharge and POT time series is used to explore the relation between flood magnitude and frequency and NAO. The results indicate that NAO is a significant covariate in explaining the magnitude and frequency of occurrence of flooding over a large part of Austria.

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“…In this paper, a methodolgy outlined in [7] was adopted, which means that the Yue-Wang (YW) modification of the nonparametric Mann-Kendall (MK) test was employed in particular. For more details the readers are referred to the original paper [8] or to [7]. Primarily, the test was applied to annual series, but also monthly series were of interest because they may reveal important changes in the seasonal course.…”

Section: Trend Test Employedmentioning

confidence: 99%

Freely available mean daily discharge series from Czechia: what can be inferred from them?

Ledvinka

2017

E3S Web Conf.

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Abstract. Most hydrometeorological data from Czechia are still provided for a fee. This especially applies to time series with a finer step than monthly. The fact that the data must be paid with respect to an expert's appraisement and that the proper licence agreement ratification has to be performed causes a considerable delay in the data transfer to potential customers, unfortunately including scientists as well. Naturally, this timeconsuming process is unpleasant to the experts on both sides. Due to a substantial rise of university students' requests for data, the Czech Hydrometeorological Institute's hydrologists launched a website from which long mean daily discharge series representing ten selected watergauging stations can be downloaded. Besides other assessments, the series may play an important role when studying climate change impacts on water resources in Czechia. Therefore, the objective here was to extract from these series some preliminary information on long-term changes such as abrupt and gradual trends caused either by the construction of reservoirs or by climate variability itself. The main tool used was nonparametric trend analysis. Mainly different months were of interest so as to determine if there have been recorded some changes in seasonality. The results may be easily expanded by students.

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The Mann-Kendall Test Modified by Effective Sample Size to Detect Trend in Serially Correlated Hydrological Series

Cited by 1,070 publications

References 30 publications

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

Understanding changes and trends in projected hydroclimatic indices in selected Norwegian and Polish catchments

Analyses of extreme flooding in Austria over the period 1951–2006

Freely available mean daily discharge series from Czechia: what can be inferred from them?

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