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Application of non parametric innovative trend analysis of different time scale precipitation during (1951-2016) in Khyber Pakhtunkhwa, Pakistan

Gul Sajid, Ren Jingli

Acta Geophysica

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2022

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Vol. 70, no 1

485--503

EN

Reliable information on the frequency and duration of excessive precipitation in foods, droughts, earthquakes, coastal foods, and hill torrents is critical to natural disaster planning and disaster risk reduction strategies. The current study examined precipitation on a monthly, seasonal, and annual scale at varying amplitudes. Moreover, the Mann–Kendall and Sen Innovative trend analysis (ITA) approaches are used to examine precipitation variations. This study aims to evaluate the Mann–Kendall and Sen Innovative Trend Analysis techniques to understand better how they apply to the topic under consideration. Overall, 84.16% of testing months showed trendless precipitation based on the MK trend test. Comparatively, the ITA monthly analysis showed statistically significant variation in 80% months and 88% considerable rate in seasonal perspective over the entire study regions. The research recognized that the Sen Innovative trend test outperforms the Mann–Kendall analysis in a range of circumstances. First of all, Sen Approach has simple assumptions, and the study of skewed distributions with fewer data could apply. Another benefit of using the ITA was that all data sets could be viewed on a graph, making it easier to see pat terns and interpret the trends. Thus, the research recommends that the Sen Trend Method (ITA) analyze monthly, seasonal, and annual precipitation patterns to facilitate water resource scheduling and establish natural disaster strategies in the future.

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Trend analysis and forecasting of the Gökırmak River streamflow (Turkey)

Arslan Gökhan, Kale Semih, Yavuz Sönmez Adem

Oceanological and Hydrobiological Studies

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2020

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Vol. 49, No. 3

230--246

EN

The objective of this paper is to determine the trend and to estimate the streamflow of the Gökırmak River. The possible trend of the streamflow was forecasted using an autoregressive integrated moving average (ARIMA) model. Time series and trend analyses were performed using monthly streamflow data for the period between 1999 and 2014. Pettitt's change point analysis was employed to detect the time of change for historical streamflow time series. Kendall's tau and Spearman's rho tests were also conducted. The results of the change point analysis determined the change point as 2008. The time series analysis showed that the streamflow of the river had a decreasing trend from the past to the present. Results of the trend analysis forecasted a decreasing trend for the streamflow in the future. The decreasing trend in the streamflow may be related to climate change. This paper provides preliminary knowledge of the streamflow trend for the Gökırmak River.

3

Sea surface temperature development of the Baltic Sea in the period 1990-2004

Siegel H., Gerth M., Tschersich G.

Oceanologia

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2006

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No. 48 (S)

119-131

EN

Sea Surface Temperature (SST) maps derived from NOAA weather satellites for the period 1990-2004 were used to investigate seasonal and inter-annual variations in the Baltic Sea. A comparison between monthly mean SST and in situ measurements at the MARNET station "Arkona Sea" showed good agreement with differences in July and August. Monthly means reflect strong seasonal and inter-annual variations. The yearly means show a slight positive trend with an increase of 0.8 K in 15 years. In particular, summer and autumn months contribute to this positive trend, with stronger trends in the northern than in the southern Baltic. The winters are characterised by a slightly negative trend. The winter minimum SST in the Arkona Sea correlates best with the WIBIX climate index derived for the Baltic region.

4

Ocena przydatności wybranych równań opisujących sezonowy przebieg parowania w Ursynowie obliczonych różnymi metodami statystycznymi

Rozbicki T., Rozbicka B.

Przegląd Naukowy Inżynieria i Kształtowanie Środowiska

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2002

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Vol. 11, No. 2

230--238

EN

The study was aimed to compare the suitability of selected statistical methods for estimation of the equations describe seasonal course of evaporation in Ursynów. Three method was considered: harmonical regression, Fourier spectral analysis and polynomial regression. Chart of the functions analysis and correlation coefficients comparision shows the best fitting for polynomial equations.