&lt;b&gt;The influence of nonlinear trends on the power of the trend-free pre-whitening approach

Blain, Gabriel Constantino

doi:10.4025/actasciagron.v37i1.18199

Cited by 25 publications

(13 citation statements)

References 34 publications

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“…Assessment of the trends observed for the quality indicators was carried out on a monthly scale using the nonparametric Mann-Kendall test [30][31][32][33]. The test is commonly employed to detect monotonic trends in a series of environmental, climate, or hydrological data.…”

Section: Significance Verification Of the Trend For The Highest Dailymentioning

confidence: 99%

Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

2018

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The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation for three significance levels: 1, 5, and 10%. Our analysis of weather conditions helped us describe the mechanism behind the formation of maximum annual daily precipitation. To analyze precipitation seasonality, we also used Colwell indices. Our study identified a significant trend of the highest daily precipitation for the assumed significance levels (0.01, 0.05, 0.1) for 22% of the investigated weather stations at different elevations. The significant trends found were positive and an increase in precipitation is expected. From 1971 to 2014, the maximum daily total precipitation most often occurred in the summer half-year, i.e., from May until September. These months included a total of 88% of days with the highest daily precipitation. The predictability index for the highest total precipitation within the area was high and exceeded 5%. It was markedly affected by the coefficient of constancy (C) and to a lesser degree by the seasonality index (M). Our analysis demonstrated a convergence of the Colwell indices and frequency of cyclonic situation and, therefore, confirmed their usability in the analysis of precipitation seasonality.

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Section: Significance Verification Of the Trend For The Highest Dailymentioning

confidence: 99%

Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

2018

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“…Trend-free pre-whitening (TFPW) is an approach that improves the performance of the M-K test in the presence of serial correlation [39]. The TFPW procedure has been proposed as a means to detect a significant trend in a time series with significant serial correlation.…”

Section: Spimentioning

confidence: 99%

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

et al. 2018

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Rainfall gauges are always sparse in the arid and semi-arid areas of Northwest China, which makes it difficult to precisely study the characteristics of drought at a large scale in this region and similar areas. This study used the TRMM (The Tropical Rainfall Measuring Mission) multi-satellite precipitation data to study the spatial-temporal evolution of drought in the Loess Plateau based on the SPI (Standardized Precipitation Index) drought index for the period of 1998-2014. The results indicate that the monthly TRMM precipitation data are well matched with the observed precipitation, indicating that this remotely sensed data set can be reliably used to calculate the SPI drought index. Based on the study findings, the average precipitation in the Loess Plateau is showing a significant increasing trend at the rate of 4.46 mm/year. From the spatial perspective, the average annual precipitation in the Southeast is generally greater than that in the Northwest. However, the annual precipitation in the Southeast area is showing a decreasing trend, whereas, the annual precipitation in the northwest areas is showing an increasing trend. Through the SPI analysis, the 3-month SPI and 12-month SPI were both showing an increasing trend, which indicates that the drought severity in the Loess Plateau was a generally declining trend at a seasonal to annual time scale. From the spatial perspective, the SPI values in the Central and Northwest of the Loess Plateau were significantly increasing, whereas, the SPI values in the southern area of the Loess Plateau were slightly decreasing. From the seasonal characteristics, the high-risk area for drought in the spring was concentrated in the northeast and southwest part, and in the summer and autumn, the high-risk area was transferred to the south part. Through this study, it is concluded that the Loess Plateau was likely getting wetter during the time period since the Grain-for-Green Project (1999-2012) was implemented, which replaced much farmland with forestry. This is a positive signal for vegetation recovery and ecological restoration in the near future.

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“…Attributes like auto-correlation and seasonality in data are problematic for the quantification of long-term trends [12]. These problems can be resolved by using a trend-free pre-whitening approach (TFPW) [17], which helps to eliminate the seasonality in data before implementation of any test for trend detection. Another approach is to practice those tests that are not affected by the seasonal cycles [18].…”

Section: Introductionmentioning

confidence: 99%

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

2018

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Abstract:The Upper Indus basin (UIB) is characterized by contrasting hydrometeorological behaviors; therefore, it has become pertinent to understand hydrometeorological trends at the sub-watershed level. Many studies have investigated the snow cover and hydrometeorological modeling at basin level but none have reported the spatial variability of trends and their magnitude at a sub-basin level. This study was conducted to analyze the trends in the contrasting hydrological regimes of the snow and glacier-fed river catchments of the Hunza and Astore sub-basins of the UIB. Mann-Kendall and Sen's slope methods were used to study the main trends and their magnitude using MODIS snow cover information (2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015) and hydrometeorological data. The results showed that in the Hunza basin, the river discharge and temperature were significantly (p ≤ 0.05) decreased with a Sen's slope value of −2.541 m 3 ·s −1 ·year −1 and −0.034 • C·year −1 , respectively, while precipitation data showed a non-significant (p ≥ 0.05) increasing trend with a Sen's slope value of 0.023 mm·year −1 . In the Astore basin, the river discharge and precipitation are increasing significantly (p ≤ 0.05) with a Sen's slope value of 1.039 m 3 ·s −1 ·year −1 and 0.192 mm·year −1 , respectively. The snow cover analysis results suggest that the Western Himalayas (the Astore basin) had a stable trend with a Sen's slope of 0.07% year −1 and the Central Karakoram region (the Hunza River basin) shows a slightly increasing trend with a Sen's slope of 0.394% year −1 . Based on the results of this study it can be concluded that since both sub-basins are influenced by different climatological systems (monsoon and westerly), the results of those studies that treat the Upper Indus basin as one unit in hydrometeorological modeling should be used with caution. Furthermore, it is suggested that similar studies at the sub-basin level of the UIB will help in a better understanding of the Karakoram anomaly.

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

Cited by 25 publications

References 34 publications

Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland

The Temporal-Spatial Characteristics of Drought in the Loess Plateau Using the Remote-Sensed TRMM Precipitation Data from 1998 to 2014

Investigating Snow Cover and Hydrometeorological Trends in Contrasting Hydrological Regimes of the Upper Indus Basin

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