Trend analysis of monthly streamflows using Şen's innovative trend method

Abstract

Trend analysis of monthly mean streamflows is essential for better water resources management and planning. In this study, Mann Kendall (MK), Sen's method and Şen's innovative trend method (ITM) were employed in order to examine the possible trends of monthly streamflows obtained from nine stations from three basins (Yakabasi and Derecikviran in Western Black Sea Basin; Durucasu, Sütlüce, Kale and Gomeleonu in Yesilirmak Basin; Şimşirli, Tozköy and Topluca in Eastern Black Sea Basin) located in Black Sea Region of Turkey. Based on the MK, streamflow data of Tozköy Station which is located in western part of the Eastern Black Sea Region showed a significantly increasing trend while a significantly decreasing trend was found for the Yakabasi, Derecikviran, Durucasu and Sütlüce stations which are situated in western part of the Black Sea Region. According to the Sen's trend method, a significantly decreasing trend was seen in Durucasu, Sütlüce, Yakabasi and Derecikviran stations while Tozköy station showed significantly increasing trend. According to the ITM, low-medium values of Tozköy Station indicated slightly increasing trend while low and medium streamflow values of Yakabasi, Derecikviran, Durucasu and Sütlüce stations showed a decreasing trend. High streamflow values of Derecikviran and Sütlüce stations showed a decreasing trend while corresponding values of Yakabasi, Şimşirli and Tozköy stations indicated an increasing trend. It was showed that trends of low, medium, and high data can be easily identified by ITM which has some advantages (having no assumption such as serial relationship, non-normality, and, test number) over the Sen's method and Mann-Kendall test.

Long-Term Homogeneity and Trends of Hydroclimatic Variables in Upper Awash River Basin, Ethiopia

“…us, the presence of trends in hydroclimatic variables may probably be due to a change in the climate. In the past few years, several studies have been conducted globally on spatial and temporal trend analyses of hydroclimatic data using nonparametric and parametric methods [16,23,25,43,60,[70][71][72][73][74][75][76][77][78]. ey mainly found that spatial-temporal trends analyses are very important for impact assessment, water resource planning and management, and adaptation of planning for extreme events (floods and droughts) in the face of climate change.…”

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

“…In addition, the innovative trend is not sensitive to serial correlation, non-linearity, and size of the time series data and gives the robust and powerful result with less error. Therefore, researchers prefer the innovative trend analysis for detecting trend in hydrological, meteorological studies 18,44,55,64,65 . Therefore, in the present study, apart from Mann-Kendall test, the innovative trend was also utilized for detecting trend.…”

Spatial distribution and estimation of rainfall trends and erosivity in the Epitácio Pessoa reservoir catchment, Paraíba, Brazil

“…Descriptive statistics techniques show the central position of the data (median) and whether there is symmetry or asymmetry in addition to showing the outliers, i.e., the values that diverge greatly from the other values in the series or are inconsistent with the series, which aid in understanding the data distribution. Among the various methods of trend analysis, two nonparametric methods were chosen: Mann-Kendall (Mann 1945;Kendall 1975), suggested by the World Meteorological Organization, and Sen's test (Sen 1968), which defines the magnitude of the trend. This integration of these two tests is used to detect significant trends and estimate the true slope of the trend.…”