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In Eastern-Indo Gangetic Plains,droughtandfloodsaremajor climatic constraints and delayed sowing of crops leads to economic losses to farming society. Climate Smart Agriculture based technologies will be an option with strong base to mitigate the ill effects of changing climate. This article deals with the climate smart agricultural technologies required to sustain agriculture in E-IGP.

The Indo Gangetic Plains (IGP) in India cover about 20% of the total geographical area (329 Mha) and producing about 50% of the total food from about 27% of net cultivated area in the country (Dhillon et al., 2010). As a part of IGP, Eastern Indo Gangetic Plains (E-IGP) comprises of Eastern Uttar Pradesh, Bihar, West Bengal, and plain parts of Assam. Major socio-economic constraints of the region are small and fragmented farm holdings, lowest per capita availability of land, inequitable agrarian structure, resource poor farmers, and poor infrastructure facilities like roads, communication power supply, storage and marketing (Singh et al., 2011). But on the other side this region is enriched with availability of fertile soils, favorable climate and an abundant supply of water through rivers and receives a fairly good amount of rainfall (1025 mm to 2823 mm). Despite of these available resources cropping intensity in the region is low and nearly 70% of land is prone to natural calamity like, heat waves, water logging, flood or drought. In addition to this farmer seems to be unable in harnessing potential yield of rice and wheat crops, majorly due to uncertainties associated with onset of rainy season, distribution of rainfall, and total rainfall in the season and inadequate water supply during peak requirement of the crop.

Intergovernmental Panel on Climate Change (IPCC) in its fourth assessment report (AR) stated that “warming of climate system is now unequivocal, as is now evident from observations of increases in global average air and ocean temperatures, widespread melting of snow and ice, and rising global sea level” (IPCC, 2007). Furthermore it reported that during last century the global average surface temperature has risen by 0.74 °C ± 0.18 °C with nearly twice linear warming trend over the last 50 years than that of previous 100 years and estimated sea level rise of 21-71 cm in the year 2070 due to thermal expansion of oceans as well as melting of glaciers. There are very good chances of decrease in rice yield up to 5 % for every 1°C rise in temperature above 32 °C (IPCC, 2007) and there will decline by 3-16 % in world agricultural productivity by 2080s (FAO, 2010). Major crops of the IGP, wheat and rice are expected to face a significant risk of reduced productivity due to a rise in winter-season temperatures and rainfall uncertainties during monsoon season. Therefore, E-IGP needs to be prepared to address the problem of feeding ever-increasing population under the climate change scenario in near future.

Observed climatic changes: The IPCC in its fifth assessment report (IPCC, 2013) had stated that “warming of the climate system is unequivocal, and since the 1950s, many of the observed changes are unprecedented over decades to millennia”. Global land and ocean surface temperature has warmed by 0.85 (0.65-1.06) °C, frequency of heat waves has increased in large parts of Europe Asia and Australia, global mean sea level rose by 0.19 (0.17- 0.21) m and GHG concentration for carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) has increased by 40%, 150%, and 20%, respectively compared to pre-industrial levels. Total radiative forcing is positive which has led to an uptake of energy by the climate system by the maximum contribution of carbon dioxide (CO₂). Since then most of the climate projections are based on the Representative Concentration Pathways (RCP) scenarios coined as RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5 leaving behind IPCC’s Special Report on Emission Scenarios (SRES) of AR4.  Both the scenarios SRES and RCPs are set in different ways, where the former provides GHG emission and land use change pathways based on underlying assumptions regarding socioeconomic drivers such as population, economy and technical development whereas, later provides radiative forcing/GHG concentration scenarios for the 21^st century. In first case atmospheric GHG concentrations derived from emissions scenarios were than later used in climatic models. In second case number attached to each RCP scenarios designates the radiative forcing in Wm^-2 by 2100 (Rummukainen, 2014). Global surface temperature changes for the end of the 21st century are likely to exceed 1.5°C relative to 1850 to 1900 for all RCP scenarios except RCP 2.6. It is likely to exceed 2°C for RCP 6.0 and RCP 8.5, and more likely than not to exceed 2°C for RCP 4.5.

It’s been reported by the scientist, researchers and validated by the IPCC that the atmosphere and ocean have warmed, amounts of snow and ice have diminished, sea level has raised, and the concentrations of greenhouse gases have increased. The 1983 to 2012 were the warmest 30 years over the northern hemisphere. GHGs present in the atmosphere beyond their natural levels have been ascribed as the major cause for climate change (Harikumar, 2016). Climate change is expected to influence crop and livestock production, hydrology and energy balance on the earth as well as input supplies and other components of the agricultural system (Singh and Pathak, 2014). When it comes to emission of GHGs besides natural factors and industrial changes it is agriculture and livestock sector is to be blamed. Rice cultivation is considered as a contributor of methane gas due to anaerobic conditions maintained during growing season of crop and livestock is considered to contribute in production of methane and nitrous oxide gases into atmosphere. Since irrigated rice is the largest source of CH₄ emission, water management in rice is the major constraint between rice production and CH4 mitigation options. Continuous flooding emits more CH₄ than alternate flooding and drying (Mishra et al., 1997) and a single midseason drainage reduces seasonal CH₄ emissions from rice fields but leads to increased emissions of N₂O (Bronson et al., 1997).

Haris et al. (2013) studied the impact of climate change on winter wheat and maize using the InfoCrop model for different time periods using HADCM3 factors at four centers in Bihar. It was found that under changed climate, wheat yield decreased whereas the yield of winter maize increased due to warmer winters and enhanced CO₂ compared to baseline. Duration of both the crops has decreased owing to the higher temperatures during the growing period. Crop duration showed maximum decline by 26 days. The increase in yield of winter maize points to the suitability of the region for its cultivation in future. Percentage decline was less in zones I and II compared to zone III. Increase in maize cultivation in locations with poor wheat yield could well be considered as an adaptation option. Sehgal et al. (2013) studies vulnerability of agriculture in 5 major states across the Indo-Gangatic plains namely Punjab, Haryana, UP, Bihar and West Bengal at district level using the indicators of exposure, potential impact, sensitivity and adaptive capacity. Over Bihar it was to found to have more changes in maximum temperature during kharif and minimum temperature during rabi from 1951-2009 along with the rainfall variability. Out of five states studies, Bihar was reported to have highest number of districts (65 % i.e. 24 out of 37) falling in extremely vulnerable category and 12 districts in high vulnerability class. Mainly Purba Champaran, Madhubani, Sitamarhi and Sheohar were found to have extreme normalized vulnerability ranging between 0.8 and 1 because of low average land-holding size (high sensitivity) and low HDI (low adaptive capacity). Tesfaye et al. (2017) in his study emphasized that Bihar’s major climate risks for crop production will be heat stress. Climate projections has indicated an annual mean temperature increase of 3.5 ° C and 5.5 ° C by 2080s over the Indian sub-continent, with the relative increase to be less in kharif (monsoon) than in the rabi (winter) season. By 2050, rainfall is projected to increase in the kharif season although it tends to decrease in the rabi season. Warwade et al. (2018) mentioned an average decline in rainfall with a rate of –2.17 mm year^–1 annually and –2.13 mm year^–1 during monsoon periods over Bihar between 1901 and 2002 along with higher numbers of negative extreme events in the later period (1957–2002) than the earlier period (1901–1956). Radhakrishnan et al. (2017) recorded positive trend for the annual and seasonal temperature with less variability of annual, summer and monsoon rainfall, moderate variability for the winter and the post-monsoon season rainfall in India during 1901–2014 and emphasizing on declining rainfall and rapid warming, especially in the last 30 years.

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Overview of Changing Climate and Need of CSA.pdf