Trend detection in rainfall and evaluation of standardized precipitation index as a drought assessment index for rice–wheat productivity over IGR in India

Abstract

ABSTRACT:The frequency and intensity of meteorological droughts over the Indo-Gangetic Region (IGR) of India pertaining to the rice crop during kharif season (June to July to October to November) and the wheat crop during the rabi season (November to December to March) were assessed using the standardized precipitation index (SPI). The monthly distribution of rainfall is more crucial than the cumulative seasonal rainfall on rice-wheat (RW) productivity. Consequently, an attempt was made to measure the effectiveness of using monthly SPI from June to September to assess drought on RW productivity over five major RW growing states of IGR in India. An attempt is also made to test the use of monthly SPI for the early kharif rice and rabi wheat forecasts for these states. The long-term mean annual rainfall of IGR is 1099.1 mm with a standard deviation of 115.7 mm and a coefficient of variation of 10.5%. It was observed that the kharif rice productivity index and monthly SPI from June to September have a significant (R 2 = 0.44) multiple regression at 0.001 level over IGR. It was also observed that in the Indo-Gangetic Region, the wheat productivity index and monthly SPI (June to September) have an insignificant (R 2 = 0.21) multiple regression. It indicated that the monthly distribution of monsoon rainfall in terms of the SPI accounted for 44% yield variability in rice and 21% yield variability in wheat. Thus, these indices may be used for forecasting the productivity of the RW system over IGR states in India.

Impacts of temperature and rainfall variation on rice productivity in major ecosystems of Bangladesh

“…This tendency was particularly high during monsoon season and almost unchanged during the dry season. Subash and Mohan [37] studied yearto-year variation in the monthly distribution of rainfall during southwest monsoon in Indo-Gangetic region for a long duration and found similar trends of rainfall patterns. The annual temperature also reports an increasing tendency; however, there are distinct differences in the trend for minimum temperature and maximum temperature (minimum temperature increased more rapidly).…”

“…Often only densely homogeneous historical-or global-scale datasets are available [20], while few assessments exist at a national level [4,16]. It is important to conduct studies at a smaller scale due to the large regional differences in surface temperature [15,20] and rainfall [37]. The IPCC [21] report highlights the need for more detailed information about climate change at regional and local scales.…”

“…Both historical observations [12,40] and climate models [37] project significant changes in DTR. DTR and SPI are important indicators in determining the impact of climate variability on crop yield [15]; hence, they were utilized in this study.…”

“…In order to study the pattern of trends and to quantify the growth rate based on technological inputs, the actual productivity was fitted with timer set linear curve over time. The technological productivity (TPi) was calculated by referring to the research of Subash and Mohan [37]:…”

The implications of geography and climate on drought trend

“…To this end, it applies the Standardized Precipitation Index (SPI), one of the parameters used to classify drought due to a climatic phenomenon (McKee et al, 1993(McKee et al, , 1995. The validity of SPI has been proven by many scholars (Hayes et al, 1999;Silva et al, 2008;Gouveia et al, 2009;Vidal and Wade, 2009;Subash and Ram Mohan, 2011).…”