Analysis of spatiotemporal rainfall variability and trend in Gilgel Gibe Watershed, Southwest Ethiopia: 1985–2017

Fanta, Sewmehon Sisay

doi:10.1007/s12517-022-10053-1

Cited by 3 publications

References 52 publications

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Comparison of sub-series with different lengths using şen-innovative trend analysis

Alashan

2022

Acta Geophys.

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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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Comparison of sub-series with different lengths using şen-innovative trend analysis

Alashan

2022

Acta Geophys.

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Assessment of water supply and demand in Gilgel Gibe watershed, southwest Ethiopia

Fanta

Namara

Yesuf

2022

Sustain. Water Resour. Manag.

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Rainfall variability analysis using precipitation concentration index (PCI) and GIS techniques over kanchipuram district of Tamilnadu, India

Sahu,

Rawat,

Alok

et al. 2024

International Conference on Intelligent and Smart Computation (Iciasc-2023)

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Analysis of spatiotemporal rainfall variability and trend in Gilgel Gibe Watershed, Southwest Ethiopia: 1985–2017

Cited by 3 publications

References 52 publications

Comparison of sub-series with different lengths using şen-innovative trend analysis

Comparison of sub-series with different lengths using şen-innovative trend analysis

Assessment of water supply and demand in Gilgel Gibe watershed, southwest Ethiopia

Rainfall variability analysis using precipitation concentration index (PCI) and GIS techniques over kanchipuram district of Tamilnadu, India

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