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      Analyzing trend and prediction of precipitation in
      Germany using non-parametrical tests and machine
      learning algorithms

      Preprint
      In review
      research-article
        1 ,
      ScienceOpen Preprints
      ScienceOpen
      precipitation, non-parametrical test, machine learning
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            Abstract

            The study explores analyzes the temporal changes in precipitation using the data from 1881 to 2020 across Germany at the regional level. Man-Kendall and Hamad-Rao modification tests were employed to analyze the precipitation trend,while Pettit test was used for detecting the change point in the time frame. Machine learning methods like k-nearest neighbour, Support vector machine and Random forest algorithms were applied for prediction. Most of the regions showed an increasing trend annually and seasonally in 0.05 significance level while some negative can be seen in summer. Furthermore, Based on Pettit test, most of the change points were detected after 1940 in several regions. In the prediction of precipitation, k-NN algorithm showed better performance in terms of mean absolute error rather than Support vector machine and Random forest algorithms.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            21 November 2021
            Affiliations
            [1 ] Environmental and Resource Management, Brandenburg University of Technolgy, Cotbbus, Germany
            Author notes
            Article
            10.14293/S2199-1006.1.SOR-.PPCPS00.v1
            ade6715a-83a2-4c4d-9f87-81d38905024a

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .


            The datasets generated during and/or analysed during the current study are available in the repository: https://github.com/talukmdm/Trend-analysis-and-prediction-of-precipitation
            General earth science,Environmental change,General environmental science
            non-parametrical test,precipitation,machine learning

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