Abstract
Precipitation is one of the key components in the water cycle. To analyse the changes in precipitation at a specific location, it is necessary to identify the distribution that best fits the precipitation data. For this purpose, three distributions i.e. generalized extreme value (GEV), generalized Pareto (GPD), and generalized logistic (GLO) were fitted to the annual precipitation data collected from 28 meteorological stations in Serbia for the period 1946–2019 using the method of L-moment. The goodness-of-fit for the selected three distributions was confirmed using the L-diagram and three measures namely relative root mean square error, relative mean absolute error, and probability plot correlation coefficient. From the results of this analysis, the GEV distribution was selected as the best fitting distribution of the annual precipitation data in Serbia. The increasing trends are presented in the western part of Serbia that can cause higher risks of floods than in other parts.
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Acknowledgements
The presented research is a part of the project of Serbian Academy of Sciences and Arts Branch in Nis (O-15-18), Erasmus+ Jean Monnet Module “EU water policy and innovative solutions in water resources management” (Ref. no. 620003-EPP-1-2020-1-RS-EPPJMO-MODULE) and also funded by the Ministry of Education, Science and Technological Development of the Republic of Serbia.
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Milan Gocic designed the initial research, conducted research and wrote initial manuscript except Introduction chapter. Lazar Velimirovic plotted plotting the graphs. Miomir Stankovic checked the statistical analysis. Slavisa Trajkovic contributed in terms of improving the initial research, writing Introduction chapter, improving the written language of the manuscript and checking the overall logical flow of the manuscript. In addition, the authors pointed out necessary comments towards improving the quality of the final manuscript.
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Gocic, M., Velimirovic, L., Stankovic, M. et al. Determining the best fitting distribution of annual precipitation data in Serbia using L-moments method. Earth Sci Inform 14, 633–644 (2021). https://doi.org/10.1007/s12145-020-00543-9
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DOI: https://doi.org/10.1007/s12145-020-00543-9