Exact distribution of the Mann–Kendall trend test statistic for persistent data

Hamed, Khaled H.

doi:10.1016/j.jhydrol.2008.11.024

Cited by 260 publications

(136 citation statements)

References 13 publications

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“…The seasonal Mann-Kendall test was used to account for the variability in water quality parameters resulting from userdefined seasons (Hamed 2009). Slope estimates for magnitude of trend (the rate of change) are the median slope of all ranked seasonal regression slopes (Chang 2008).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Mei

Liao

Zhu

et al. 2014

Environ Sci Pollut Res

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Water quality degradation is often a severe consequence of rapid economic expansion in developing countries. Methods to assess spatial-temporal patterns and trends in water quality are essential for guiding adaptive management efforts aimed at water quality remediation. Temporal and spatial patterns of surface water quality were investigated for 54 monitoring sites in the Wen-Rui Tang River watershed of eastern China to identify such patterns in water quality occurring across a rural-suburban-urban interface. Twenty physical and chemical water quality parameters were analyzed in surface waters collected once every 4-8 weeks from 2000 to 2010. Temporal and spatial variations among water quality parameters were assessed between seasons (wet/dry) and among major land use zones (urban/suburban/rural). Factor analysis was used to identify parameters that were important in assessing seasonal and spatial variations in water quality. Results revealed that parameters related to organic pollutants (dissolved oxygen (DO), chemical oxygen demand (manganese) (COD Mn ), and 5-day biochemical oxygen demand (BOD 5 )), nutrients (ammonia nitrogen (NH 4 + -N), total nitrogen (TN), total phosphorus (TP)), and salt concentration (electrical conductivity (EC)) were the most important parameters contributing to water quality variation. Collectively, they explained 70.9 % of the total variance. A trend study using the seasonal Kendall test revealed reductions in COD Mn , BOD 5 , NH 4 + -N, petrol, V-phen, and EC concentrations over the 11-year study period. Cluster analysis was employed to evaluate variation among 14 sampling sites representative of dominant land use categories and indicated three, three, and four clusters based on organic, nutrient, and salt water quality characteristics, respectively. Factors that are typically responsible for water quality degradation (including population, topography, and land use) showed no strong correlation with water quality trends implying considerable point source inputs in the watershed. The results of this study help inform ongoing water quality remediation efforts by documenting trends in water quality across various land use zones.

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Section: Discussionmentioning

confidence: 99%

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Mei

Liao

Zhu

et al. 2014

Environ Sci Pollut Res

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“…The advantage of this method is that the data does not conform to any particular distribution, and it has a low sensitivity to abrupt breaks, due to the inhomogeneous time series [31]. It is often used for trend detection in a long time series of meteorological and hydrological records [32][33][34][35]. For a time series X = { , , ... }, the Mann-Kendall test statistic is calculated as…”

Section: Mann-kendall Methodsmentioning

confidence: 99%

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

Zhao

et al. 2014

Remote Sensing

149

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Fractional vegetation cover (FVC) is an important biophysical parameter of terrestrial ecosystems. Variation of FVC is a major problem in research fields related to remote sensing applications. In this study, the global FVC from 1982 to 2011 was estimated by GIMMS NDVI data, USGS global land cover characteristics data and HWSD soil type data with a modified dimidiate pixel model, which considered vegetation and soil types and mixed pixels decomposition. The evaluation of the robustness and accuracy of the GIMMS FVC with MODIS FVC and Validation of Land European Remote sensing Instruments (VALERI) FVC show high reliability. Trends of the annual FVC max and FVC mean datasets in the last 30 years were reported by the Mann-Kendall method and Sen's slope estimator. The results indicated that global FVC change was 0.20 and 0.60 in a year with obvious seasonal variability. All of the continents in the world experience a change in the annual FVC max and FVC mean , which represents biomass production, except for Oceania, which exhibited a significant increase based on a significance level of p = 0.001 with the Student's t-test. Global annual maximum and mean FVC growth rates are 0.14%/y and 0.12%/y, respectively. The trends of the annual FVC max and FVC mean based on pixels also illustrated that the global vegetation had turned green in the last 30 years. A significant trend on the p = 0.05 level was found for 15.36% of the GIMMS FVC max pixels on a global scale (excluding permanent OPEN ACCESSRemote Sens. 2014, 6 4218 snow and ice), in which 1.8% exhibited negative trends and 13.56% exhibited positive trends. The GIMMS FVC mean similarly produced a total of 16.64% significant pixels with 2.28% with a negative trend and 14.36% with a positive trend. The North Frigid Zone represented the highest annual FVC max significant increase (p = 0.05) of 25.17%, which may be caused mainly by global warming, Arctic sea-ice loss and an advance in growing seasons. Better FVC predictions at large regional scales, with high temporal resolution (month) and long time series, would advance our ability to understand the characteristics of the global FVC changes in the last 30 years and predict the response of vegetation to global climate change.

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“…In Equations (6) and (7), the M-K method defines the statistical amount S and variance V(S). It also assumes that it follows the normal distribution [19,30]:…”

Section: The Mann-kendall (M-k) Rank Correlation Methodsmentioning

confidence: 99%

“…If β > 0, it means the time sequence has a rising tendency; if β < 0, it means the time sequence has a decreasing tendency [30].…”

Section: The Mann-kendall (M-k) Rank Correlation Methodsmentioning

confidence: 99%

Annual Precipitation Fluctuation and Spatial Differentiation Characteristics of the Horqin Region

et al. 2017

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Abstract:Precipitation is the main water source for vegetation survival in arid and semi-arid areas. However, previous studies always focus on the effects of precipitation in different time scales, but ignore the effects of precipitation in different spatial scales. To further study the effects of precipitation fluctuation in different spatial scales, we used the wavelet analysis method to analyze its temporal and spatial change based on data from eighteen meteorological stations during 1961-2015 in Horqin region. Results showed that: (1) from the overall tendency of precipitation changes, the precipitation inter-annual variations in Horqin region had the tendency of gradually decreasing from the southeast (District IV) to the northwest; (2) the precipitation anomalies of District I-IV between 1960 and 1980 were small and approximate to the normal value; (3) in the time scale of 23-32 years, the cyclical fluctuations were very significant and the annual precipitation underwent two cyclical fluctuations from a period of low precipitation to a period of high precipitation; and (4) as results of analyzing the spatial wavelet variance of sub-region, the main cycle of precipitation in District I, District II and District III was between 10 and 11 years, while the main cycle of precipitation in District IV was 25 years. The main conclusions include the following. (1) This region tended to be arid, and the precipitation gradually decreased from the southeast (District IV) to northwest (District I). (2) The influence of spatial differentiation characteristics on precipitation fluctuation in this region was cyclical fluctuation, which gradually decreased from the southeast to the northwest. The length of the cyclical change period gradually shortened. In the first main cycle, whose annual precipitation changes were most significant, the changing characteristic was District IV and District I decreased from 25 years to 10 years. (3) Predicated from the cyclical changing law that the annual precipitation decreases from high to low, the Horqin region will remain in a period of low precipitation between 2016 and 2020.

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Exact distribution of the Mann–Kendall trend test statistic for persistent data

Cited by 260 publications

References 13 publications

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Evaluation of Spatiotemporal Variations of Global Fractional Vegetation Cover Based on GIMMS NDVI Data from 1982 to 2011

Annual Precipitation Fluctuation and Spatial Differentiation Characteristics of the Horqin Region

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