Farmers in India and across the world are witnessing new variations in weather and seasonal changes. The challenge to take decisions under these variations gets compounded because often there is no precedent to it. What decisions work best can be known through experimentation and mostly in hindsight. This makes adaptation to climate change a complex process. The cause-effect conundrum, i.e. which solution gives what result is almost impossible to predict with certainty. Thus, human decision making under such unforeseen situations needs to be aided by additional information or decision support systems. Climate Services, the delivery of weather based agriculture advisories using ICT, help aid farmer’s decision making process by providing timely weather forecasts and corresponding advisories on agricultural practices.
The information farmers receive on climate services provides them with an option of incorporating it into their agriculture decision making. But it is almost impossible to measure with certainty how much of this information do they incorporate, in what form and when. This makes impact evaluation of adaptation solutions, like climate services, a very challenging exercise. At times even the farmers are unable to clearly demarcate the important variables they use for their decision making process. This is so because in order to cope with weather variations there are many possible actions and solutions to be experimented with. But the most effective solutions may not be known to them at the early stages and thus their decision making keeps evolving as they experiment with a set of solutions. Through this process of iterative decision making they learn to adapt to weather variations. This makes adaptation a highly localized and continuous process with no clear traces of solution impact pathways. But a set of good practices evolve over time.
Challenges to measure or generate evidence of adaptation further hinder the uptake and popularity of good practices. There is also a theoretical difficulty in establishing units for measuring adaptation and establish monitoring systems for its evaluation. This makes communicating adaptation through evidence a very difficult task. It also challenges the imagination of policy makers who mostly rely on numbers for estimating impacts. For example, the climate mitigation negotiations use the 2°C limit of temperature rise as the reference for determining how much emissions need to be reduced to achieve this climate goal. But in case of adaptation there is a dearth of quantifiable numbers which could guide the policy planning process. Thus, policy making for adaptation requires a shift of two kinds
1) Moving away from relying only on numbers, and
2) Decentralization of policy making to account for localized adaptation processes.
This shift further brings up two challenges
1) How to measure what is intangible or un-measured, and
2) At what scale should the policy making process be localized.
Unless research on climate change adaptation focuses to find answer to these two challenges, policy making for adaptation to climate change would remain a very challenging task.
Note: This article was first posted on my linkedin on October 3, 2016 for TERI’s World Sustainable Development Summit 2016. Link: https://www.linkedin.com/pulse/challenge-policy-making-climate-change-adaptation-mihir-mathur/