4.1 Extreme temperature events and their impacts on rice
The increasing trends of temperature (mean Tmax, mean Tmin) in coastal Odisha will harm soil health and agriculture production (Brevik 2013; Karmakar et al. 2016). The rise in mean temperature is a cause of concern especially night temperature as it affects agricultural crop growth and yield (Cruz et al. 2007). Many studies have proven that the increasing minimum temperature (night temperature) affect respiration in rice plants, and can potentially reduce biomass accumulation and crop yield through increasing plant respiration (Hatfield et al. 2011; Das et al. 2014; Shi et al. 2017). Drought stress during flowering stage could cause upto 80% yield loss in rice (Senapati et al. 2019). The increasing warm nights and warm days will bring early crop maturity thereby reduce the effective grain filling period in crops and affect the crop yield and quality (Akter and Islam 2017). For example, the extremely high temperature in 2010 after heading significantly reduced rice grain quality in many rice-growing regions of Japan (Morita et al. 2016). Plants exposed to high nighttime temperatures during the grain development period experienced lower productivity and reduced quality (Hatfield et al. 2014). The exposure of rice crop to heat stress (warm days & warm nights) during grain filling stage will increase chalkiness of the grains by increasing the air spaces between amyloplasts as a result of loosely packed starch granules (Ashida et al. 2009) which could result in a higher percentage of broken grains and significantly lower market value of the rice grain (Lyman et al. 2013; Zhao and Fitzgerald 2013). The decreasing CSDI and cool night signify, shortening of winter and widening of summer in coastal districts. This result is even supported by the fact that increasing mean Tmax, mean Tmin and WSDI in coastal Odisha. The negative value of DTR signifies narrowing down of the difference between the maximum and minimum temperatures. The reduced diurnal temperature range has been shown to affect crop growth and development of rice crop (Peng et al. 2004; IPCC 2007; Bahuguna and Jagadish 2015).
4.2 Extreme rainfall events and their impacts on rice
Though coastal Odisha receives higher rainfall than its country average, its distribution is not good especially during the cropping season. In general, the total annual rainfall in coastal Odisha is increasing over a year. The increasing trend of heavy precipitation (R64.5), very heavy precipitation (R124.5) and decreasing trend of R2.5 makes clear that the increased annual precipitation is mainly because of the increased number of heavy rainy days and very heavy rainy days. It is obvious from the result that, the distribution of rainfall in the coastal district of Odisha is changed, due to decreased number of rainy days and increased heavy precipitation, very heavy precipitation day and SDII which intern responsible for the increased number of CDD, and frequency of drought and floods. A similar result of increasing total annual rainfall in coastal districts of Odisha is also reported by Sahu and Khare (2015). The increasing number of R64.5 and R124.5 and decreasing number of rainy days (R2.5) may also be correlated with an increased number of flood events in coastal districts.
SDII indicates the mean precipitation in wet days and the results shows, increasing mean precipitation amount during wet days. The decreased number of rainy days and increasing trend of SDII, heavy rainfall, very heavy rainfall signifies poor distribution of rainfall. The probability for drought is more with increasing CDD, similarly, the probability for flood is more with increasing CWD. It is obvious from the result that, the decreased number of rainy days and increased heavy precipitation and very heavy precipitation day and which intern increased CDD, and frequency of drought and floods. The increasing frequency of drought and flood in coastal Odisha intern reduces the agriculture production and causes huge economic loss.
The calculation of consecutive precipitation amount is more important to overcome the adverse effect of heavy and very heavy rainfall on agriculture production. The success/failure of agriculture crop during a rainy period is largely controlled by consecutive day precipitation (rainfall distribution). If the precipitation in consecutive days is more than it causes flooding in the crop field. However, the impact of flooding on the crop depends on so many factors like soil characteristics (initial soil moisture, slope, texture, organic matter), crop characteristics (stage of the crop, crop root zone depth, crop canopy cover) and environment (temperature, wind, relative humidity). The high water table in rice weakened root, stem and leaves (Dahiya 2018).
In general, the consecutive day precipitation in coastal districts is increasing. The increased consecutive day precipitation causes flooding in rice and reduces the grain yield. The effect of consecutive days rainfall is more pronounced in clay soil and, less pronounced in sandy soil since the later soil has more permeability than earlier one (Witheetrirong et al. 2011). In coastal Odisha, rice is established by two methods viz., direct seeding and conventional transplanting. Direct seeded rice (DSR) is sown during the first fortnight of June, whereas transplanting of rice is done during the second fortnight of July to first fortnight of August. In DSR the flowering of rice occurs from the second fortnight of September to first fortnight of October. Similarly, in transplanted rice flowering occur in October (Das 2012). Though rice is tolerant of a waterlogging for a short period, the consecutive heavy rain during flowering causes lodging of crop plants and chaffy grains (Rawson and Macpherson 2000). Germination and flowering periods are the most vulnerable to rainfall anomalies (Bacci 2017). Flowering time is a critical stage of development in the life cycle of rice plants because the seed number is determined (Bacci 2017). There are many methods to compute effective rainfall. In this study, we consider Indian-2 method and Vietnam method assumption for computing effective rainfall. According to Vietnam method, a daily rainfall < 5 mm and > 50 mm is considered as ineffective. Similarly, two-days and three-days successive rainfall of > 60 mm and 70 mm is considered as ineffective rainfall respectively (Ali and Mubarak 2017). In Indian-2 method, a daily rainfall < 6.25 mm and ten-days consecutive rainfall of > 125 mm is treated as ineffective (Ali and Mubarak, 2017). Month wise computation of consecutive rainfall in coastal districts shows the amount of rainfall received during June to October in all the coastal district is mostly > 100 mm. In coastal districts flowering generally coincide in the month August and most vulnerable to moisture stress. Flood during flowering will cause lodging of the rice plant and yield loss.
4.3 Relationship between rice grain yield and extreme events
The rice yield and extreme events graph clearly show the negative relationship between grain yield and number of extreme events of different types. The rice yield in all the districts decreased sharply when the number of extreme events increased (Fig. 15). The graph shows the decreasing grain yield is not just function one or two extreme events instead it is often the cumulative effect of multiple stress events during the crop growing period. It also shows that even in the normal rainfall years the grain yield is reduced if the distribution of rainfall is uneven. The reduced grain yield is obserbed even in normal rainfall years having increased number of heavy precipitation, very heavy precipitation, and higher consecutive day rainfall events. The increasing number of CDD shows the increasing chance of moisture stress and poor distribution of rainfall. In case of normal rainfall years, high-temperature stress viz., warm days and warm night have reduced the rice grain yield significantly. The climate smart technology including tolerant varieties is suggested for ensuring the resilience of the production system.