Kodandarama,, S.R. and Mohan Kumar,, T.L. and Prathima,, C.M. and Krishna, T. V. (2024) Analysis of Rainfall Trend in North Interior Karnataka (NIK) Meteorological Subdivision of Karnataka by Non-Parametric Methodologies. Asian Research Journal of Agriculture, 17 (2). pp. 60-69. ISSN 2456-561X
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Abstract
The present study analyzed the trend in the month-wise, seasonal and annual rainfall employing three non-parametric tests viz. Mann-Kendall (M-K), Modified Mann-Kendall (MM-K) tests and Sen’s slope estimator for North Interior Karnataka (NIK) meteorological subdivision of Karnataka using 60 years (1960-2019) rainfall data. The M-K test results revealed that there is no monotonic trend in all data sets which indicates that there may exist the influence of serial correlation in the rainfall data. The MM-K test was applied to rainfall data of the NIK subdivision, the result of the test revealed that January, February, March and August months have a monotonic increasing trend whereas April, May, July and September months have a monotonic decreasing trend whereas June, October, November and December have no monotonic trend in monthly rainfall data. The winter season has a monotonic increasing trend, monsoon and post-monsoon seasons have a monotonic decreasing trend, and the pre-monsoon season has no monotonic trend in seasonal rainfall data. The MM-K test statistic (Tau) value for the NIK (-0.12) subdivision was found to be significant and negative indicating that there is a monotonic decreasing trend. Larger negative Sen’s slope values for NIK (-1.40) subdivision indicate the high decreasing rate of change of rainfall for annual rainfall data. Therefore, to know the trend in rainfall data most accurately in the presence of outliers and serial correlation, the Modified Mann-Kendall (MM-K) test and Sen’s slope estimator are recommended instead of Mann-Kendall (M-K) and Sen’s slope estimator.
Item Type: | Article |
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Subjects: | Universal Eprints > Agricultural and Food Science |
Depositing User: | Managing Editor |
Date Deposited: | 16 Mar 2024 06:12 |
Last Modified: | 16 Mar 2024 06:12 |
URI: | http://journal.article2publish.com/id/eprint/3671 |