Spatio-temporal trends and variability of rainfall in Maharashtra, India: Analysis of 118 years
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ORIGINAL PAPER
Spatio-temporal trends and variability of rainfall in Maharashtra, India: Analysis of 118 years RN Singh 1
&
Sonam Sah 2 & Bappa Das 3 & Lata Vishnoi 4 & H. Pathak 1
Received: 29 June 2020 / Accepted: 3 November 2020 # Springer-Verlag GmbH Austria, part of Springer Nature 2020
Abstract This study examined the spatio-temporal trends and variability of seasonal and annual rainfall for 36 districts of Maharashtra, India. For this purpose, 118 years (1901 to 2018) gridded rainfall data of India Meteorological Department (IMD) were analyzed using Mann-Kendall (MK), modified Mann-Kendall (MMK), Sen’s slope (SS), Spearman’s rank correlation (SRC), simple linear regression (SLR), and innovative trend analysis (ITA). Auto-correlation coefficient was calculated at lag-1 and tested at 5% level of significance. Rainfall variability was examined using the coefficient of variation (CV). The analysis revealed significantly decreasing trends for winter and pre-monsoon rainfall in districts of Maharashtra. Monsoon, post-monsoon, and annual rainfall had both increasing and decreasing trends. Out of 185 time series analyzed, ITA detected trends in 168 (90.8%) time series. All the trends detected by MK/MMK, SRC, and SLR were captured by ITA, along with trends in additional 103 (55.6%) time series which were not captured by any of the aforesaid methods. Rainfall variability was very high in all the districts for winter, pre-monsoon, and post-monsoon seasons. The trends and variability analysis of rainfall in the state along with their maps would be useful for the local stakeholders for planning efficient use of water resources.
1 Introduction Change in the amount and distribution of rainfall is one of the major impacts of climate change that deserves immediate attention and systematic study. The rising global temperatures over the last century is expected to continue resulting in droughts and decreasing rainfall (IPCC 2013). As rainfall is one of the primary components of the hydrological cycle, understanding its variability and trend is important to understand the vital aspects in climatological, hydrological, industrial, meteorological, and agricultural studies worldwide (Xia et al. 2015; Chatterjee et al. 2016; Yang et al. 2017;Meshram et al. 2017; Bisht et al. 2018; Malik and Kumar 2020). Study
* RN Singh [email protected] 1
ICAR-National Institute of Abiotic Stress Management, Baramati, Maharashtra, India
2
G.B. Pant University of Agriculture & Technology, Pantnagar, Uttarakhand, India
3
ICAR-Central Coastal Agricultural Research Institute, Goa Old Goa, India
4
India Meteorological Department, Lodhi Road, New Delhi, India
of significant climatic changes, especially changes in the occurrence and distribution of rainfall, is also necessary for sustainable water management which requires accurate knowledge of long-term rainfall trends and variability ( Zolina et al. 2010; Fatichi et al. 2013; Sun et al. 2018). In recent years, several studies have been conducted on spatio-temporal trends and its m
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