Linking Farmer's Participation with Modeling Approach to Study the Impact of Climate Change and to Identify the Suitable Adaptation Strategies for Rice-Wheat Production System in Igb.

Climate change impacts are increasingly visible in India, with greater variability of the monsoon. Seasonal mean rainfall shows inter-decadal variability, noticeably a declining trend with more frequent deficit monsoons.  The climate model projections based on IPCC AR5 CMIP5 models, reveal that surface air temperatures including night time temperatures are expected to further increase. The all-India rainfall is also expected to increase due to increased moisture availability. However, extreme rainfall events are also expected to increase in future. Under the business-as-usual scenario, mean warming over India is likely to be in the range 1-7-2.0⁰C by 2030s and 3.3-4.8⁰C by 2080s relative to pre-industrial times. All-India precipitation under the business-as-usual scenario is projected to increase from 4%  to 5% by 2030s and from 6% to 14% towards the end of the century (2080s) compared to the 1961-1990 baseline. Under such situation, the agricultural productivity will decrease and there by threat to food security and livelihoods of many small and marginal farmers.  The smallholders constitutes 86 per cent of the total agricultural households.

Under this scenario, we have taken up a case study under AgMIP-ICAR Collaborative project,  at Meerut District (29⁰4’ N, 77⁰ 46’ E, 237 m ASL), part of the Upper Gangetic region of the IGP, India to analyze the productivity, farm net return and per capita income under future climate by coupling climate-crop-economic models.  This study is based on the farm survey (2012) data relating to 76 rice-wheat growing farm households in Meerut district of the North-West India in the Indo-Gangetic Basin (IGB). We have used outputs of five GCMs (CCSM4, GFDL-ESM2M, HadGEM2-ES, MIROC5, MPI-ESM-MR) for the mid-century period (2040-2069) under RCP8.5.   The APSIM7.5 and DSSAT4.5 crop simulation models were used for yield simulation under baseline as well as future climate scenarios.  The TOA-MD (Trade-off-analysis and minimum data set) model used for economic analysis.  It is found that all the five GCMs predicted  higher monthly mean maximum and minimum temperatures during the rice and wheat growing season compared to baseline (1980-2010).  It is also clear that there is lot of uncertainty in the case of monsoon rainfall projections by different GCMs.  

There is lot of uncertainty among the impact of climate change on rice and wheat projections due to uncertainty in GCMs as well as due to the difference in sensitivity of DSSAT and APSIM with temperature and CO₂.  The current agricultural production system under climate change scenario would experience a decline in mean rice yield of the order of 8–23 percent with APSIM. However, DSSAT simulations shows both decline (4–19% under climate scenario GFDL-ESM2M, HadGEM2-ES & MPI-ESM-MR) as well as increase in mean yield (2–5% for climate scenario CCSM4 & MIROC5). In case of wheat, the mean yield changes shows similar trend. While APSIM estimates shows decline in mean yield of wheat (17-29%), DSSAT shows increase in mean yield (6-15 percent). On the basis of Representative Agricultural Pathways (RAPS) - which is the visualization of future by the stakeholders of the district and also with the available empirical evidences on climate change impact on livestock sector, it was assumed that milk yield is likely to decline by 10 percent. Accordingly, the percentage gains in mean net farm returns are higher under DSSAT (13-32%) as compared to APSIM (11-12%) in all five climate scenario for the current agricultural production system. Overall, the mean net farm returns are likely to decline by 12-17% percent under APSIM and 3-9 percent under DSSAT under the five climate scenarios. Similarly, the per capita income would decline approximately by 8-11 percent and 2-6 percent as per APSIM and DSSAT estimates, respectively under five climate scenarios. As expected, the population poverty rates would increase by about 1- 4% under climate change. 

Based on farmers survey and stakeholder interactions, we have identified advancing of date of sowing to 10-days is one of the important adaptation package to avoid the exposing of wheat crop to severe heat conditions during the milky/dough phase of the crop.  It is projected that there will be 5-15 % increase in rice-wheat system yield when we incorporate one adaptation strategy and thereby increase of 9- 13 percent in mean farm returns, and poverty would further decline by about two percentage point, based on TOA-MD analysis. For more accurate impact assessment of agricultural productivity, there is a need to incorporate more crops,  vegetables and livestock simulations in the system.