54
in the remaining season, lead to the deficit of available water that may result in severe
dry. Thus, changes in characteristics of summer monsoon would have an effective
impression on water resource management, agricultural production and overall economy of these countries (Jain et al. 2013). Therefore, analysis of detail rainfall characteristics, for example, rainfall seasonality, precipitation concentration and trend are
integral part of discussion of any climatologist and environmental geographer.
In any study on climate change, the determination of trend gains the utmost importance in the hydro-meteorological time series to resolve objectively whether the
trends are increasing, decreasing or neutral behaviour. But the evaluation of concentration, seasonality and trend were exceptionally troublesome using time series data
because of its non-linear nature. However, few significant studies were carried out
worldwide on rainfall trend in the last and recent decades by Zhai et al. (2005), Chu
et al. (2010), Gocic and Trajkovic (2013), Fathian et al. (2015), Rahman et al. (2017)
and Sa’adi et al. (2019). The changes in precipitation patterns and degree of concentration may influence agricultural productivity, energy production, soil erosion, storm
water drainage and so on (Caloiero 2014). Some studies have shown that occurrences
of extreme precipitation events and associated disasters have significantly amplified
day by day. A minor change in mean precipitation can result in a comparatively high
intensification in the chance of extreme precipitation (Groisman et al. 1999). Thus,
precipitation intensity, amounts, frequency and spatio- temporal variation have gained
much attention. Oliver (1980) suggested that the knowledge of precipitation is
extremely important and thus offered a precipitation concentration index (CI) to
assess the contribution of extreme rainfall to the total volume. Precipitation concentration characteristics using precipitation concentration index (PCI), precipitation
concentration period (PCP) and precipitation concentration degree (PCD) were analysed by several researcher such as Wang et al. (2003), Zhang and Qian (2003), Li
et al. (2011), Chatterjee et al. (2016), Huang et al. (2018). A good number of studies,
on the other hand, were made over India and Bangladesh separately by researchers
using various models where significant increasing trend was observed by Goswami
et al. (2006), Shahid (2010), Alam and Iskander (2013), Kamruzzaman et al.
(2016), Jaswal et al. (2015) and Abdul Quadir et al. (2016), while decreasing trend
was observed by Ahasan et al. (2010), Rahman et al. (2015), Bari et al. (2016), Shah
and Mishra (2016), Basher et al. (2018), Meshram et al. (2018), Das and Bhattacharya
(2018) and Das et al. (2019; 2020). However, the results illustrated that those studies
had a good ability to simulate the trends of rainfall or rainfall extreme that can be
approved with assurance for the impact of the change of climate.
Therefore, this study aimed to identify the seasonality, concentration pattern and
trends of rainfall in Bangladesh and India. To accomplish this study, we used precipitation concentration index (PCI) (Oliver 1980), rainfall seasonality index (SI) (Walsh
and Lawler 1981), innovative trend analysis (ITA) (Sen 2012) method and non-parametric Mann-Kendall (MK) (Mann 1945; Kendall 1975) test or modified MK (Hamed
and Rao 1998) test based on the properties of the observation data. The slope of the
changes was estimated by Sen’s estimator (Sen 1968). MK and mMK tests are the
robust methods for identifying trends in hydro-meteorological variables and can be
applied in missing data (Tabari et al. 2012; Nalley et al. 2013; Rahman et al. 2018;
Das et al. 2019) while ITA method has universal contextually in comparison to MK
T. Mandal et al.
in the remaining season, lead to the deficit of available water that may result in severe
dry. Thus, changes in characteristics of summer monsoon would have an effective
impression on water resource management, agricultural production and overall economy of these countries (Jain et al. 2013). Therefore, analysis of detail rainfall characteristics, for example, rainfall seasonality, precipitation concentration and trend are
integral part of discussion of any climatologist and environmental geographer.
In any study on climate change, the determination of trend gains the utmost importance in the hydro-meteorological time series to resolve objectively whether the
trends are increasing, decreasing or neutral behaviour. But the evaluation of concentration, seasonality and trend were exceptionally troublesome using time series data
because of its non-linear nature. However, few significant studies were carried out
worldwide on rainfall trend in the last and recent decades by Zhai et al. (2005), Chu
et al. (2010), Gocic and Trajkovic (2013), Fathian et al. (2015), Rahman et al. (2017)
and Sa’adi et al. (2019). The changes in precipitation patterns and degree of concentration may influence agricultural productivity, energy production, soil erosion, storm
water drainage and so on (Caloiero 2014). Some studies have shown that occurrences
of extreme precipitation events and associated disasters have significantly amplified
day by day. A minor change in mean precipitation can result in a comparatively high
intensification in the chance of extreme precipitation (Groisman et al. 1999). Thus,
precipitation intensity, amounts, frequency and spatio- temporal variation have gained
much attention. Oliver (1980) suggested that the knowledge of precipitation is
extremely important and thus offered a precipitation concentration index (CI) to
assess the contribution of extreme rainfall to the total volume. Precipitation concentration characteristics using precipitation concentration index (PCI), precipitation
concentration period (PCP) and precipitation concentration degree (PCD) were analysed by several researcher such as Wang et al. (2003), Zhang and Qian (2003), Li
et al. (2011), Chatterjee et al. (2016), Huang et al. (2018). A good number of studies,
on the other hand, were made over India and Bangladesh separately by researchers
using various models where significant increasing trend was observed by Goswami
et al. (2006), Shahid (2010), Alam and Iskander (2013), Kamruzzaman et al.
(2016), Jaswal et al. (2015) and Abdul Quadir et al. (2016), while decreasing trend
was observed by Ahasan et al. (2010), Rahman et al. (2015), Bari et al. (2016), Shah
and Mishra (2016), Basher et al. (2018), Meshram et al. (2018), Das and Bhattacharya
(2018) and Das et al. (2019; 2020). However, the results illustrated that those studies
had a good ability to simulate the trends of rainfall or rainfall extreme that can be
approved with assurance for the impact of the change of climate.
Therefore, this study aimed to identify the seasonality, concentration pattern and
trends of rainfall in Bangladesh and India. To accomplish this study, we used precipitation concentration index (PCI) (Oliver 1980), rainfall seasonality index (SI) (Walsh
and Lawler 1981), innovative trend analysis (ITA) (Sen 2012) method and non-parametric Mann-Kendall (MK) (Mann 1945; Kendall 1975) test or modified MK (Hamed
and Rao 1998) test based on the properties of the observation data. The slope of the
changes was estimated by Sen’s estimator (Sen 1968). MK and mMK tests are the
robust methods for identifying trends in hydro-meteorological variables and can be
applied in missing data (Tabari et al. 2012; Nalley et al. 2013; Rahman et al. 2018;
Das et al. 2019) while ITA method has universal contextually in comparison to MK
T. Mandal et al.