In recent time, climate change is a serious environmental issue posing serious threats to human being. Though, the natural change of climatic parameters (e.g. rainfall, temperature, humidity) follow a naturalistic rhythm, but rapid anthropogenic greenhouse gas (GHGs) emissions since post-industrial era in particular causing global warming as well as climate change (IPCC 2014,Sam and Chakma 2019). As a consequence global surface temperature has increased nearly 0.6 ± 0.2°C in the 20th century since 1861 (Kumar et al. 2014).In association with the global warming the rainfall changes have already been recorded across the globe. Several global studies (IPCC 2014, Ren et al. 2013, Adler et al. 2017) reported increasing rainfall trend with an increasing inconsistency. However, such change may not be identical at regional level, since both the increasing and decreasing trends have reported from different parts of the world (Bhutiyani et al. 2010; Rana et al. 2012). Decreasing trend of rainfall observed in Tanzania (Gebrechorkos et al. 2019), north and central Ethiopia (Asfaw et al. 2018), North China (Su et al. 2020), middle India (Duhan and Pandey 2013), Pakistan (Salma et al. 2012) and in Bangladesh (Khan et al. 2019). On the contrary, increasing trends reported from Southern and Central China (Choi et al. 2009), Srilanka (Nisansala et al. 2020), and arid East-Central Asia (Hong et al. 2014). Such changes in rainfall adversely affected regional crop production system as well as food security, biodiversity, livelihood and human health (Connell 2015).
As a principle elements of hydrological cycle, rainfall directly affects runoff, fresh water availability and thus water demand in various sectors (drinking, domestic, irrigation, industry, hydro-power generation) of a region (Padron et al. 2020). Voudouris et al. (2012) estimated that a decrease in rainfall by 20% will reduce runoff by 29–32% in Crete region and subsequent dearth of freshwater availability of the region. Any abrupt change in annual rainfall affect spatio-temporal allocation of runoff, moisture content in the soil, ground water storage, stream flow and water quality (Das et al. 2014). Besides, anomalies in rainfall distribution bring series of environmental consequences such as soil erosion, landslide, flood, and drought etc. (Gupta et al. 2014). Having low resiliency and adaptive capacity developing countries are the hardest hit of climate changes, since majority of the population relay on the climate sensitive economic activities like agriculture, fishing and tourism etc. (Mandal et al. 2018).
In India, agrarian economy largely depends on the normal distribution of rainfall, more than 80% of which occurs during monsoon months (June to September). Spatio-temporal anomalies in the Southwest Monsoon rainfall (SWM) pose serious threats to the agricultural production system vis-à-vis Indian economy. The SWM rainfall over India was in decreasing trend during 21st centuries, while increasing trend observed in pre-monsoon and post-monsoon season (Ghosh and Dutta 2020). It was evident that the deficit of 23% in SWM rainfall (2009–2010) adversely affected Kharif production and thus decline of agricultural GDP by 0.2% compare to the previous year in India (Aggarwal 2010). Another report warns that the crop production will reduce by 31.3% with the reduction of rainfall by 2030 in India (Vyankatrao 2017). However, at sub-regional scale Das et al. (2014) reported increasing trend in summer monsoon rainfall and rainy days over east coast and Deccan Plateau, while decreasing trend in west coast, eastern part, western desert region and northeastern region of India during 1971 to 2005. Guhathakurta and Rajeevan (2008) reported significant decrease in annual rainfall for the subdivisions of Konkan and Goa, Madhya Maharashtra, North Interior Karnataka, Rayalseema, coastal Andhra Pradesh, Gangetic West Bengal, Assam, Meghalaya and Jammu and Kashmir.during 1901 to 2003. However, for the country as a whole the annual and monsoon rainfall decreased and winter rainfall increased during 1871 to 2005 (Kumar et al. 2010). In a study of 236 districts rainfall data (1901–2000), Bera (2017) showed that the half of the Ganga basin experienced decrease in annual rainfall, while significant declining trend in annual, pre-monsoon and post-monsoon rainfall over Kosi, Gandak and Sone sub-basins. Basistha et al. (2009) reported increase of annual rainfall over Indian Himalayan region during 1902–1964, while decrease in between 1965–1980. Narayanan et al. (2016) reported rise in pre-monsoon rain over Ajmer, Bikaner, Indore, Kolkata and fall in Minicoy, Belgaum during 1949–2009. Kamal and Pachauri (2019) observed negative trend in annual rainfall over northeast India during (1901–2015), though the state of Meghalaya and Mizoram experienced significant positive trend in SWM rainfall and Arunachal Pradesh, Assam, Nagaland and Sikkim felt significant decrease.
Likewise, in West Bengal wide variation of annual as well as seasonal rainfall occurrences likely to be observed and any abrupt change in rainfall distribution affected predominant agricultural system. Thus, the proper knowledge of inter annual and seasonal rainfall variability, their trends and anomalies through the sound analysis of long period rainfall dataset would be of immense utility in devising agricultural planning and water resource management. However, literatures available in public domain for the lower Gangetic plains (Chatterjee et al. 2016; Mukhopadhyay et al. 2016; Kundu and Mondal 2019; Ghosh and Dutta 2020) are with shorter data period excluding resent years data. Though the availability of long term observed rainfall dataset is another challenge especially in West Bengal, where well spaced rain gauge stations, preservation of long period data, and data availability in public domain is rare. Secondly quality control of available data and data analysis with standard methods is another challenge. Keeping this in mind, we aimed at analysing the spatio-temporal anomalies in rainfall occurrences, annual and seasonal trends and magnitude of rainfall distribution across the districts of West Bengal, India. We used long period grided (0.5o× 0.5o) rainfall dataset (1901–2020) and employed Mann-Kendal (Mann 1945; Kendall 1975) non-parametric trend test and Sen’s slope estimator (Sen 1968).