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Comparison of sub series with diferent lengths using şen innovative trend analysis

Alashan Sadık

Acta Geophysica

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2023

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Vol. 71, no. 1

373--383

EN

Climate change causes trends in hydro-meteorological series. Traditional trend analysis methods such as Mann-Kendall and Spearman Rho are sensitive to dependent series and cannot detect non-monotonic trends. Şen-innovative trend analysis method is launched into literature in order to overcome these restrictions. It does not require any restrictive assumptions as serial independence and normal distribution and examines a given time series as equally divided into two sub-series. The Şen multiple innovative trend analysis methodology is improved to detect partial trends on different sub-series, again with equal lengths. Climate change strongly affects hydro-meteorological parameters today compared to the last twenty or thirty years and gives asymmetrical trend change points in hydro-meteorological 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, the Şen innovative trend analysis method is revised to satisfy these requirements (ITA_DL). The new approach compared with the traditional Mann-Kendall (MK) and Şen innovative trend analysis (Şen_ITA) gives successful and consistent results. The ITA_DL gives four monotonic trends on May, July, September, and October rainfall series of Oxford although the MK gives three mono tonic trends in the May, July, and December and cannot detect trends on the September and October. In the ITA_DL visual inspection, the December rainfall series does not show an overall or partial trend. The ITA_DL trend results are consistent with the Şen_ITA except for the September rainfall series, although it has different trend slope amounts.

2

The Short-Term and Seasonal Trend Detection of Sediment Discharges in Turkish Rivers

Burgan Halil Ibrahim

Rocznik Ochrona Środowiska

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2022

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Tom 24

214--230

EN

Hydrometeorological variables are tested by trend methods to detect trends in river basins. Mann-Kendall and Spearman’s rho tests are widely used as traditional trend methods. Besides, some new trend tests are applied to hydrometeorological variables, such as Innovative Trend Analysis (ITA). Sediment discharge observations are more complicated than other hydrometeorological variables. In general, sediment data are observed on a monthly time scale. Therefore, there are minimal studies on sediment data, especially in Turkey. In this study, Innovative Trend Analysis (ITA), Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann-Kendall trend analyses are applied to sediment discharges in Turkish river basins. According to Mann-Kendall, Correlated Mann-Kendall and Seasonal Mann-Kendall results, positive trends have detected only 8, 2 and 20 gauging stations, respectively. Then, 30 positive and 15 negative trends were detected by ITA methodology. The trend slopes calculated from ITA methodology are categorised because some positive and negative trends are weak. The applied trend methods are evaluated together, considering the climate properties of hydrological regions in Turkey. Increasing trends in sediment data are detected from the rivers in the Mediterranean region of Turkey. The results of the study would help to manage water resources as well as sustainable development in the Turkish river basins.

3

Temporal and spatial trend analysis of rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat, India

Patel Pratik S., Rana Shilpesh C., Joshi Geeta S.

Acta Geophysica

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2021

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Vol. 69, no. 1

353--364

EN

Global warming is a biggest issue around the world. In this research paper, the temporal and spatial trend analysis of seasonal and annual rainfall on Bhogavo River watersheds in Sabarmati lower basin of Gujarat state of India has been analysed using the data of 11 rain gauge stations installed in Bhogavo watershed. Linear regression, Mann–Kendall Test, Sen’s slope test and innovative trend analysis methods are used to carry out monthly and annual rainfall trend analysis. In addition to the rainfall analysis, a number of rainy days change in magnitude as a percentage of mean rainfall have also been analysed using linear regression and Sen’s slope method, respectively. The IDW method is used to develop a spatial distribution of annual and seasonal rainfall trend over the study area. From the results, it is concluded that annual rainfall shown increasing (positive) trend at nine stations out of 11 stations. The highest value of change in magnitude of trend as a percentage of mean monthly rainfall has been obtained in the month of July, attributing increasing trend at Sayla station and lowest value magnitude of trend as a percentage of mean rainfall in the monthly rainfall has been obtained in the month of August, attributing decreasing trend at Bavla station.

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Climate change impacts on sea surface temperature (SST) trend around Turkey seashores

Dabanli Ismail, Şişman Eyüp, Güçlü Yavuz Selim, Birpınar Mehmet Emin, Şen Zekai

Acta Geophysica

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2021

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Vol. 69, no. 1

295--305

EN

This paper focuses on sea surface temperature (SST) trends due to the importance of temperature diference in climate change impact research. These trends are not only essential for climate, but they are also important for marine ecosystem. Immigration of fsh population due to the temperature changes is expected to cause unexpected economical results. For this purpose, both classical Mann–Kendall, (MK) (Mann in Econom: J Econom Soc 13:245–259, 1945; Kendall in Rank Correlation Methods, Charless Grifn, London, 1975) and innovative trend analysis (ITA) (Şen in J Hydrol Eng 17(9):1042–1046, 2012) methodologies are applied for the SST data records. Monthly SST data are considered along the Black, Marmara, Aegean, and Mediterranean coastal areas in Turkey. SST data are categorized into fve clusters considering fsh life as “hot,” “warm-hot,” “warm,” “cold,” and “very cold.” According to ITA, SST in all coastal areas tends to increase except for winter season during “very cold” (0–10 °C) temperatures. The temperature changes in both winter and summer seasons are expected to change the marine life, fsh population, tourism habit, precipitation regime, and drought feature.