Agrarian Adaptation in North India

Full Title

Modelling adaptation and vulnerability to climate risks from the ground-up: A case of smallholder agriculturalists across North India

Abstract

There is an urgent need for policy makers to design comprehensive and robust adaptation policies for agricultural households in the Global South, facing climate risks—including changes in temperature and precipitation, droughts, and floods. Today, many promoted policies implement standardized adaptation programs, which cater to certain farmers but also neglect others who might not be able or willing to partake in proposed strategies. These programs are therefore incomplete and do not attend to the broader set of vulnerabilities faced by diverse households. This project asks: How can policy makers develop comprehensive adaptation policies across regional socio-environmental systems using information on the processes of adoption of potential adaptation strategies for individual farmers?

Using baseline farmer surveys collected by the CGIAR program on Climate Change Agriculture and Food Security (CCAFS) in the North Indian region, this project uses statistical analyses and social modeling tools, namely Agent-Based Models, to model the emergent adaptation behavior of 1,400 farmers. This behavior is in response to hydro-meteorological and climatic risks, which we model using indicators such as their risk perceptions, livelihoods, access to resources, socioeconomic status, and other social variables (religion, culture, education etc.). Our proposed research addresses the significant methodological challenge of understanding system-wide and dynamic regional adaptation behavior among individual farm households. This research provides policy makers with information on key cross-scale dynamics to better develop specific and tailored adaptation programs that reflect the reality of household decision-making contexts, and it supports diverse and differentiated farmer adaptation decisions.

Project Type
Team Synthesis Project (Graduate Student Led)
Date
2016
Principal Investigators
Udita Sanga
Sameer Shah, University of British Columbia
Participants
Hogeun Park, Michigan State University
Courtney Hammond Wagner, University of Vermont
Lia Helena Monteiro de Lima Demange, University of São Paulo
Caroline Gueiros, Oxford University
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