Sowtime: Climate Adaptive Agriculture in the Eastern Gangetic Plains

Agricultural transformations have increased food production five-fold in South Asia, but that progress has not been realized in the Eastern Indo-Gangetic Plains (EGP), a region spanning India, Nepal, and Bangladesh. Meeting future food demand while coping with climate change will require substantial adaptation by EGP farmers. But we know little about the nature or outcomes of agricultural adaptations by EGP farmers, and even less about future possibilities. Our proposed research will answer the question: What is the adaptive potential of smallholder agriculture in the EGP? Our central hypotheses are: 1) Smallholder farmers have already adapted to a changing climate by planting earlier, adopting faster maturing varieties, and switching crop types. 2) These adaptive practices have mitigated the effect of climate change on crop yields. And, 3) additional transformations will further increase crop yields and resilience but socioeconomic barriers prevent widespread adoption. We will test these hypotheses by combining innovative remote sensing analyses, statistical and biophysical crop yield modeling, in-region field data collection, and causal analyses of fused household survey and remote sensing datasets. We will quantify contemporary cropping patterns and practices, and the extent and spatiotemporal variation of adaptive strategy adoption with remotely sensed assets and available ground and administrative data from regional partners. The effect of future climate change under various scenarios of agricultural adaptation will be quantified using climate projections and yield models. These analyses are integrated with a household survey and choice experiments that will reveal farmer’s attitudes towards climate change, adaptive agricultural practices, and the barriers to further transformation.
Our effort will produce annual cadence, finely resolved maps of crop types, including the characterization of multicropping rotations, the timing and duration of critical crop growth stages, and changes in these variables over the period 2001-present. No existing products map these variables at the scale of individual smallholder fields, and for the time period and temporal cadence necessary to evaluate the adaptive potential of the EGP. We will create these products using a newly developed approach to data fusion capable of assimilating a wide variety of heterogeneous satellite imagery, including newly available high resolution commercial assets. We will use phenology algorithms to extract the timing of growth stages, and emerging approaches to classification that use a Bayesian framework to assimilate existing heterogeneous crop type maps and ancillary data. Statistical and biophysical crop yield models will be fit, driven by historical weather and downscaled climate projections, and used to quantify the climate mitigating effects of adaptive practices. Our household surveys and analysis of map products will guide the design of realistic future scenarios of agricultural adaptation.
By characterizing and quantifying the adaptive potential of smallholder agriculture in the EGP, our study will support decision makers, regional food and water security, efforts to alleviate rural poverty, and the adoption of feasible climate adaptive strategies. Our project will further develop and apply innovative remote sensing methodologies such as data fusion and classification approaches, and will thus be useful to the broader remote sensing science community. Additionally, because the goals of our project are well-aligned with those of several large initiatives like SARIN, CIMMYT, and GEOGLAM, we expect our results to find a broad audience with the means and impetus to ensure they support on-the-ground change, and ultimately, a more sustainable and resilient food future for the EGP.