Please use this identifier to cite or link to this item: http://nopr.niscair.res.in/handle/123456789/54423
Title: Long term spatial and temporal rainfall trend analysis using GIS and statistical methods in Lower Bhavani basin, Tamil Nadu, India
Authors: Anand, B.
Karunanidhi, D.
Keywords: Groundwater Management;Lower Bhavani Basin;Mann-Kendall Test;Rainfall;Spatial fluctuation
Issue Date: Mar-2020
Publisher: NISCAIR-CSIR, India
Abstract: The present study aims to identify the long term spatial and temporal distribution of rainfall, using the methods from GIS and statistical tools, in Lower Bhavani basin. For this attempt, the spatial distribution of rainfall pattern was studied, by using 33 years of rainfall data (1983 – 2015), from 22 rain gauge stations. The rainfall pattern was interpolated by Inverse Distance Weighted (IDW) method using Arc GIS 10.2.1 on the monthly, seasonal and annual basis. The mean annual rainfall of the region was 666.84 mm. The increasing monthly rainfall was reported in the month of October (164 mm) and decreasing rainfall was observed in the month of January (4.99 mm). The seasonal rainfall changes were prominent during the north east Monsoon season. From 1983 to 2015, 2010 witnessed the highest rainfall pattern in the area. The statistical analysis of Mann Kendall (MK) Test was used, to detect the monotonic increasing and decreasing trend over time, on a monthly basis. A significant level (α = 0.05) was used to detect the positive and negative trend that existed over the basin. To be precise, the positive trend existed during the October over 10 rain gauge stations and it was located on the upper northern part of the basin. The negative trend was observed, over six rain gauge stations in southern part of the basin, in the month of January. The result indicated that spatial distribution of rainfall and trend pattern ensured influences in the topography, agriculture productivity and groundwater management across the basin.
Page(s): 419-427
URI: http://nopr.niscair.res.in/handle/123456789/54423
ISSN: 0975-1033 (Online); 0379-5136 (Print)
Appears in Collections:IJMS Vol.49(03) [March 2020]

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