Mann‐Kendall (MK) trend test is frequently employed as the most familiar trend detection method. Its application requires serial independence of available hydrometeorological time series records. As suggested in the literature, the serial correlation effect can be removed from the given time series by using prewhitening, variance correction or overwhitening processes such as in the modified Mann‐Kendall (MMK) procedure. The PW process may cause some of the current trends to be removed along with the serial correlation. In this study, the MMK method is supported by Şen innovative trend analysis instead of Sen slope estimator (SSE). The MMK method is applied to monthly maximum temperatures of Oxford station in England, for which the data length is large and the moving trend slope values are calculated starting from 1854 for all durations between 1873 and 2017. The MMK_SSE and MMK_ITA methods yield significant increasing trends between 0.0037 and 0.0125°C/year annual slopes for January, March, May, July, August, September, October, November, December, but for February, there is not any significant trend. While MMK_SSE does not give any significant trend for April that has maximum positive kurtosis and skew, but MMK_ITA reflects an increasing trend of 0.0059°C per year.
This study discusses the temporal distribution of earthquake magnitudes in the city of Bingöl, near Karlıova Triple Junction. We determine the probability distributions and return periods of earthquakes for all districts of Bingöl. Bingöl has eight districts; namely Adaklı, Central, Genç, Karlıova, Kiğı, Solhan, Yayladere, and Yedisu. In six of them, active faults were mapped previously (Adaklı, Central, Genç, Karlıova, Solhan, and Yedisu). We consider 5 time-dependent probability distributions for analysis. Using the annual maximum earthquake magnitudes, the best fit arises from the Gumbel distribution for Central, Karlıova, and Adaklı Districts. For the Genç District, where the least maximum earthquake magnitude is reported, the Weibull distribution gives the best fit. The return period and maximum annual earthquake magnitude relations suggest the following results. For the Central and Karlıova Districts along which maximum earthquake magnitudes are reported, every 250 years a 6.7 M, and 7.2 M occurs respectively. These results are compatible with the results of paleo-seismological data reported along the NAFZ and the EAFZ. For a 10-year return period, earthquake magnitudes reach 3.9 and 5.1 in all districts. It is important to note that in the Yedisu District, the maximum earthquake magnitudes seem as 5.1 M for the 1000-year return period, incompatible with previously published findings probably because low quality seismic data in this region.
Güneşin yeryüzünün farklı bölgelerini farklı ısıtmasından dolayı meydana gelen rüzgâr olayının, bulutların taşınarak yağmurların oluşması, çiçek tozlarının taşınarak döllenmesi, yenilenebilir ve temiz enerji kaynağı olarak kullanılma gibi birçok faydası mevcuttur. Bu çalışmada Bingöl ili ortalama rüzgâr hızları ve günümüzde meydana gelen iklim değişikliğinin etkisi araştırılmıştır. Ayrıca çalışmada Bingöl ili üzerinde hâkim olan rüzgâr yönü ve esen rüzgârın hangi yönden ne kadar sürekli olduğu araştırılmıştır. Rüzgâr hızı potansiyeli belirleme çalışmaları literatürde çok fazla yer almasına karşın bu potansiyelin iklim değişikliği ve/veya şehirleşme karşısında davranışını belirleme çalışmaları güncelliğini korumaktadır. Bu çalışma iki aşamada gerçekleşmekte olup birinci aşamada rüzgar hızı potansiyeli belirlenmiş, ikinci aşamada ise bu potansiyelin gelecekteki davranışı incelenmiştir. İklim değişikliği ve/veya şehirleşmenin etkilerini araştırmak üzere literatüre yeni kazandırılan ve birçok araştırmacı tarafından kullanılan yenilikçi yönelim çözümlemesi (YYÇ), geleneksel doğrusal regresyon (DR) ve Mann-Kendall (MK) yöntemleri kullanılmıştır. Yapılan çalışmalar sonucunda Bingöl ilinin genel olarak kuzeybatı yönünden rüzgârlarla beslendiği ve rüzgâr potansiyelinin tüm aylarda azalma eğiliminde olduğu ve söz konusu üç yönteminde birbirleri ile tutarlı sonuçlar verdiği tespit edilmiştir.
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.
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