Spatial and temporal characteristics of monthly rainfall over Limbang River Basin, Northern Borneo: an evaluation throug
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ORIGINAL ARTICLE
Spatial and temporal characteristics of monthly rainfall over Limbang River Basin, Northern Borneo: an evaluation through multivariate statistics M. V. Ninu Krishnan1 · M. V. Prasanna1 · H. Vijith1 Received: 6 April 2020 / Accepted: 21 May 2020 © Springer Nature Switzerland AG 2020
Abstract Identification of homogeneous rainfall regime in Limbang River Basin (LRB), Malaysia, Northern Borneo and its temporal characteristics were elucidated in the present study. Multivariate statistical techniques were used to characterize 15 years (2000–2015) monthly rainfall data from twelve rain gauging stations present in LRB. Analysis of monthly accumulated rainfall indicates that LRB receives maximum rainfalls during January, April, November, December and least in July. Three dominant clusters (C1, C2 and C3) of homogeneous rainfall were identified by Ward’s method of hierarchical clustering, and multivariate statistics were applied to understand its temporal characteristics. Comparing the clusters formed in different elevations in LRB, cluster-3 which covers middle catchment region shows the highest accumulated monthly (487 mm in November) and annual rainfall (4571 mm). At the same time, all the clusters shown more or less similar pattern of temporal rainfall distribution with varying dispersion and skewness and these altogether contribute 74% of annual rainfall received by LRB. Though the study area is considered as unique climatic (equatorial tropical rainforest) regime, the observed variation in rainfall among the clusters can be attributed to the factors such as locations of rain gauging stations (elevation and geomorphology), characteristics of hills/mountains, proximity to ocean and wind characteristics in the region. The findings of present research will serve as an essential pre-requisite dataset for any hydrological development program in the river basin. Keywords Cluster analysis · Multivariate · Whisker plots · Temporal analysis · Skewness
Introduction Rainfall, the most important component of precipitation which controls the hydrologic regime in the earth, is undergoing rapid changes in its spatial and temporal characteristics due to climate change in recent decades. (Negash et al. 2013). In order to understand the effect of climate change over the hydrometeorological variables, scientists used statistical trend analysis to elucidate the behavior of rainfall, temperature, evaporation, rainy days, non-rainy days and stream flow-related discharge characteristics (Zhai and Pan 2003; Partal and Kahya 2006; Ogolo 2011; Yazdani et al. 2011; Das et al. 2014; Zhang et al. 2015; Chelcea et al. 2016; * M. V. Ninu Krishnan [email protected] 1
Department of Applied Geology, Faculty of Engineering and Science, Curtin University Malaysia, CDT 250, 98009 Miri, Sarawak, Malaysia
Tarek et al. 2016; Tian and Yang 2017; Bajracharya et al. 2018; Yaseen et al. 2018; Sa’adi et al. 2019; Wang et al. 2020). Findings from these studies helped to develop the strategies to mitigate adverse effects of climate
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