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Article type: Research Article
Authors: Thangmawia, L. | Lalpawimawha, | Vanlalhriatsaka, ; * | Kumar, Anupam | Thanhmingliana, ; * | Zoramthanga, R. | Ranjan, Mukesh | Denghmingliani, | Duhawma, L.P. | Zothanpuia,
Affiliations: Department of Mathematics, Pachhunga University College, Mizoram University, Aizawl, Mizoram | Department of Statistics, Pachhunga University College, Mizoram University, Aizawl, Mizoram | Department of Chemistry, Pachhunga University College, Mizoram University, Aizawl, Mizoram | Department of Biotechnology, Pachhunga University College, Mizoram University, Aizawl, Mizoram
Correspondence: [*] Corresponding Author. [email protected]
Abstract: Analysing rainfall patterns in Mizoram from 1998 to 2017 reveals diverse trends. The highest average rainfall occurred in 2004, reaching 292.8 mm, while 2014 marked the lowest at 151.77 mm. Siaha District experienced the highest average rainfall (3020.2 mm), while Champhai District had the lowest (1663 mm). In 2017, the Kendall method showed correlations between temperature and relative humidity, rainfall and relative humidity, but not between rainfall and temperature. Cluster analysis, a technique partitioning datasets into cohesive groups, was applied to Mizoram’s district-wise rainfall data using single, complete, and average linkage methods. The Single Linkage Method formed one large cluster with under 26% similarity and the shortest distances between data points. The complete linkage method divided districts into two clusters with under 26% similarity and maximal inter-cluster distance. The Average Linkage Method merged all districts into one cluster with under 26% similarity and minimised inter-cluster distances. Comparing the techniques, Single and Complete Linkage Methods proved most effective for Mizoram’s district-wise rainfall data. With only eight districts, forming additional clusters remained limited. This analysis highlights the significance of rainfall patterns in agricultural ecosystems and the utility of statistical methodologies like cluster analysis in understanding long-term trends.
Keywords: Mizoram, rainfall, dendrogram, cluster analysis
DOI: 10.3233/AJW240062
Journal: Asian Journal of Water, Environment and Pollution, vol. 21, no. 5, pp. 73-83, 2024
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