scholarly journals Comparison of Sub-Series with Different Lengths Using Şen-Innovative Trend Analysis

2021 ◽  
Author(s):  
Sadık Alashan
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Visual Inspection ◽  
Meteorological Parameters ◽  
Rainfall Series ◽  
Analysis Method ◽  
New Approach ◽  
Trend Analyses ◽  
Innovative Trend Analysis ◽  
Main Series

Abstract Climate change causes trends in hydro-meteorological series. Traditional trend analysis methods such as Mann-Kendall and Spearman Rho are sensitive to correlated series and cannot detect non-parametric trends. Şen-innovative trend analysis method is launched to literature in order to overcome these restrictions. It does not require any restrictive assumptions as serial dependence and normal distribution and examines a main series as equally divided two sub-series. Şen multiple innovative trend analyses methodology is improved to detect partial trends on different sub-series but again equal lengths. Climate change nowadays more effects hydro-meteorological parameters according to last two or three decades and gives asymmetric trend change point on main time series. Due to asymmetric trend change points, it may be necessary to analyze sub-series with different lengths to use all measured data. In this study, Şen innovative trend analyses method is revised for these requirements (ITA_DL). The new approach compared with traditional Mann Kendall (MK) and Şen innovative trend analysis (Şen_ITA) gives successful and consistent results. ITA_DL gives four monotonic trends on Oxford May, July, September and October rainfall series although MK gives three monotonic trends on May, July and December and cannot detect trends on September and October. In the ITA_DL visual inspection, the December rainfall series does not show a trend that is monotonic or non-monotonic. Şen_ITA trend results are consistent with ITA_DL except September, although there are different trend slopes.

scholarly journals Analysis of total monthly precipitation of Susurluk Basin in Turkey using innovative polygon trend analysis method

2020 ◽  
Author(s):  
Gokmen Ceribasi ◽  
Ahmet Iyad Ceyhunlu
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
Meteorological Parameters ◽  
Global Climate ◽  
Data Series ◽  
Monthly Precipitation ◽  
Precipitation Data ◽  
Analysis Method ◽  
Distinctive Features ◽  
Monthly Precipitation Data

Abstract The effects of climate change caused by global warming can be seen in changes of climate variables such as precipitation, humidity, and temperatures. These effects of global climate change can be interpreted as a result of the examination of meteorological parameters. One of the most effective methods to investigate these effects is trend analysis. The Innovative Polygon Trend Analysis (IPTA) method is a trend analysis method that has emerged in recent years. The distinctive features of this method compared with other trend methods are that it depends on time series and can compare data series among themselves. Therefore, in this study, the IPTA method was applied to total monthly precipitation data of Susurluk Basin, one of Turkey's important basins. Data from ten precipitation observation stations in Susurluk Basin were used. Data were provided by the General Directorate of State Meteorology Affairs. The length of this data series was 12 years (2006–2017). As a result of the study, since there is no regular polygon in IPTA graphics of each station, it is seen that precipitation data varies by years. While this change is seen increasingly at some stations, it is seen decreasingly at other stations.

scholarly journals Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1855 ◽  
Author(s):  
Ali ◽  
Kuriqi ◽  
Abubaker ◽  
Kisi
Keyword(s):  
Trend Analysis ◽  
Yangtze River ◽  
Winter Season ◽  
Trend Test ◽  
Analysis Method ◽  
Adaptation Measures ◽  
Minimum Flow ◽  
Mk Test ◽  
Innovative Trend Analysis ◽  
Increasing Trend

Trend analysis of streamflow provides practical information for better management of water resources on the eve of climate change. Thus, the objective of this study is to evaluate the presence of possible trends in the annual, seasonal, maximum, and minimum flow of Yangtze River at Cuntan and Zhutuo stations in China for the period 1980 to 2015. The assessment was carried out using the Mann–Kendall trend test, and the innovative trend analysis, while Sen’s slope is used to estimate the magnitude of the changes. The results of the study revealed that there were increasing and decreasing trends at Cuntan and Zhutuo stations in different months. The mean annual flow was found to decrease at a rate of −26.76 m3/s and −17.37 m3/s at both stations. The minimum flow was found to significantly increase at a rate of 30.57 m3/s and 16.37 m3/s, at a 95% level of confidence. Maximum annual flows showed an increasing trend in both regions of the Yangtze River. On the seasonal scale, the results showed that stations are more sensitive to seasonal flow variability suggesting a probable flooding aggravation. The winter season showed an increasing flow trend, while summer showed a decreasing trend. The spring flow was found to have an increasing trend by the Mann–Kendall test at both stations, but in the Zhutuo Station, a decreasing trend was found by way of the innovative trend analysis method. However, the autumn flow indicated a decreasing trend over the region by the Mann–Kendall (MK) test at both stations while it had an increasing trend in Cuntan by the innovative trend analysis method. The result showed nonstationary increasing and decreasing flow trends over the region. Innovative trend analysis method has the advantage of detecting the sub-trends in the flow time series because of its ability to present the results in graphical format. The results of the study indicate that decreasing trends may create water scarcity if proper adaptation measures are not taken.

scholarly journals Tropical rainfall trend and stationarity analysis

2020 ◽  
Vol 20 (7) ◽  
pp. 2471-2483
Author(s):  
Chun Kang Ng ◽  
Jing Lin Ng ◽  
Yuk Feng Huang ◽  
Yi Xun Tan ◽  
Majid Mirzaei
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Spatial Scales ◽  
Kendall Test ◽  
Temporal Analysis ◽  
Northern Region ◽  
Rainfall Series ◽  
Kelantan River Basin ◽  
Temporal And Spatial

Abstract Climate change is most likely to cause changes to the temporal and spatial variability of rainfall. A trend analysis to investigate the rainfall pattern can detect changes over temporal and spatial scales for a rainfall series. In this study, trend analysis using the Mann–Kendall test and Sen's slope estimator was conducted in the Kelantan River Basin, Malaysia. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test was applied to evaluate the stationarity of the rainfall series. This basin annually faces onslaughts of varying year-end flooding conditions. The trend analysis was applied for monthly, seasonal and yearly rainfall series between 1989 and 2018. The temporal analysis results showed that both increasing and decreasing trends were detected for all rainfall series. The spatial analysis results indicated that the northern region of the Kelantan River Basin showed an increasing trend, whilst the southwest region showed a decreasing trend. It was found that almost all the rainfall series were stationary except at two rainfall stations during the Inter Monsoon 1, Inter Monsoon 2 and yearly rainfall series. Results obtained from this study can be used as reference for water resources planning and climate change assessment.

scholarly journals Innovative Trend Analysis of Annual and Seasonal Rainfall Variability in Amhara Regional State, Ethiopia

Atmosphere ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 326 ◽  
Author(s):  
Mohammed Gedefaw ◽  
Denghua Yan ◽  
Hao Wang ◽  
Tianling Qin ◽  
Abel Girma ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Seasonal Variability ◽  
Rainfall Variability ◽  
Seasonal Rainfall ◽  
Annual Rainfall ◽  
Series Data ◽  
Analysis Method ◽  
Study Region ◽  
Regional State ◽  
Innovative Trend Analysis

This study investigated the annual and seasonal rainfall variability at five selected stations of Amhara Regional State, by using the innovative trend analysis method (ITAM), Mann-Kendall (MK) and Sen’s slope estimator test. The result showed that the trend of annual rainfall was increasing in Gondar (Z = 1.69), Motta (Z = 0.93), and Bahir Dar (Z = 0.07) stations. However, the trends in Dangla (Z = −0.37) and Adet (Z = −0.32) stations showed a decreasing trend. As far as monthly and seasonal variability of rainfall are concerned, all the stations exhibited sensitivity of change. The trend of rainfall in May, June, July, August, and September was increasing. However, the trend on the rest of other months showed a decreasing trend. The increase in rainfall during Kiremt season, along with the decrease in number of rainy days, leads to an increase of extreme rainfall events over the region during 1980–2016. The consistency in rainfall trends over the study region confirms the robustness of the change in trends. Innovative trend analysis method is very crucial method for detecting the trends in rainfall time series data due to its potential to present the results in graphical format as well. The findings of this paper could help researchers to understand the annual and seasonal variability of rainfall over the study region and become a foundation for further studies.

scholarly journals Innovative Trend Analysis of Air Temperature and Precipitation in the Jinsha River Basin, China

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3293
Author(s):  
Zengchuan Dong ◽  
Wenhao Jia ◽  
Ranjan Sarukkalige ◽  
Guobin Fu ◽  
Qing Meng ◽  
...  
Keyword(s):  
Climate Change ◽  
Trend Analysis ◽  
River Basin ◽  
Air Temperature ◽  
Climatic Factors ◽  
Trend Detection ◽  
Spatial Pattern Analysis ◽  
Jinsha River ◽  
Temperature And Precipitation ◽  
Innovative Trend Analysis

Trend detection based on hydroclimatological time series is crucial for understanding climate change. In this study, the innovative trend analysis (ITA) method was applied to investigate trends in air temperature and precipitation over the Jinsha River Basin (JRB), China, from 1961 to 2016 based on 40 meteorological stations. Climatic factors series were divided into three categories according to percentile, and the hidden trends were evaluated separately. The ITA results show that annual and seasonal temperatures have significantly increased whereas the variation range of annual temperature tended to narrow. Spatial pattern analysis of the temperature indicates that high elevation areas show more increasing trends than flat areas. Furthermore, according to ITA, significant increase trends are observed in annual precipitation and “high” category of spring precipitation. The sub-basins results show a significant decreasing trend in elevation zones of ≤2000 m and an increasing trend where elevation is >2000 m. Moreover, linkage between temperature and precipitation was analyzed and the potential impact of the combined changes was demonstrated. The results of this study provide a reference for future water resources planning in the JRB and will help advance the understanding of climate change in similar areas.

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