Non-parametric trend analysis of water quality data of rivers in Kansas

Basin-wide assessment of temperature trends in northwest and central India / Estimation par bassin versant de tendances de température au nord-ouest et au centre de l'Inde

“…Kundzewicz & Robson (2004) provide general guidance to the methodology of change detection in time series of hydrological records. To identify trend in the climatic variables with reference to climate change, the Mann-Kendall test has been employed by a number of researchers with temperature, precipitation and streamflow data series (Taylor & Loftis, 1989;McLeod et al, 1991;Yu et al, 1993;Burn, 1994;Douglas et al, 2000;Yue et al, 2003;Burn et al, 2004;Lindström & Bergström, 2004;Xiong & Guo, 2004). This commonly used nonparametric test was applied in this study to determine monotonic trends in different variables.…”

Disentangling the Relationships between Net Primary Production and Precipitation in Southern Africa Savannas Using Satellite Observations from 1982 to 2010

“…It is a non-parametric test which can address the time series with seasonal variation, having missing values, tied values, or outliers, and does not require normality of the time series [34]. It is widely used in the field of hydrology to evaluate the significance of trends in time series such as water quality, stream flow, and precipitation [34][35][36].…”

“…It is a non-parametric test which can address the time series with seasonal variation, having missing values, tied values, or outliers, and does not require normality of the time series [34]. It is widely used in the field of hydrology to evaluate the significance of trends in time series such as water quality, stream flow, and precipitation [34][35][36]. This method is developed from the Mann-Kendall test which is based on the correlation between the ranks of a time series and their time order, but is improved to be able to use seasonal data sets to address variability [34].…”

“…It is widely used in the field of hydrology to evaluate the significance of trends in time series such as water quality, stream flow, and precipitation [34][35][36]. This method is developed from the Mann-Kendall test which is based on the correlation between the ranks of a time series and their time order, but is improved to be able to use seasonal data sets to address variability [34]. The seasonal Kendall test was conducted on the per-pixel NPP time series to obtain the spatial pattern of changing trends.…”

A comparison of the power of thettest, Mann-Kendall and bootstrap tests for trend detection / Une comparaison de la puissance des teststde Student, de Mann-Kendall et du bootstrap pour la détection de tendance

“…ven Belle & Hughes, 1984;Cailas et al, 1986;Hipel et al, 1988;Hipel & McLeod, 1994;Taylor & Loftis, 1989;Demarée & Nicolis, 1990;Zetterqvist, 1991;Chiew & McMahon, 1993;Yu et al, 1993;Hirsch et al, 1993;Lettenmaier et al, 1994;Burn, 1994;Yulianti & Burn, 1998;Gan, 1998;Lins & Slack, 1999;Douglas et al, 2000;Yue et al, 2003; and others). Another rank-based nonparametric test, the Spearman's rho (SR) test (Lehmann, 1975;Sneyers, 1990), has sometimes been applied to detect trends in hydrological data (e.g.…”