Can Seasonal Climate Forecast Improve the Food Security Under Changing Climate?: A Case Study from Tamil Nadu State in India.

Seasonal climate forecasts (SCF) have the potential to increase the economic performance of agriculture and/or reduce risks associated with climate.  SCF can be utilized at a range of scales from agricultural policy making down to the field scale. SCF provides opportunity for farmers to modify their strategic farming decisions around crop and variety choice, land allocation among different crops and land configuration to minimize the effects of adverse weather events or to realize opportunities within favorable seasons. SCF can be used to modify off-farm decisions on input sourcing/distribution, stock maintenance, subsidy and yield forecasting by agriculture departments. While SCF have the potential to support agricultural decision-making, they are inherently challenging due to their probabilistic nature. To investigate the value of SCF in agricultural decision-making, a study was undertaken with stakeholders (farmers, agriculture department officials, input suppliers) of Dindigul District, Tamil Nadu. Capacity of stakeholders to understand probabilistic SCF was enhanced through use of decision analysis theory and role-playing. Concerted effort was made to communicate the forecast information by representing different probabilities of seasonal rainfall starting from climatological scenario of equal chances of normal, dry and wet season. Given a forecast of 60% normal, 20% dry and 20% wet season, farmers were asked to articulate their crop and varietal choice. To illustrate the potential complexity of integrating SCF, producer company members articulated their business plan on climatically risky decision of managing seed supply chain in the region. They make demand-side decisions (quantity of seeds of different crops/varieties to be procured, spreading out the quantity of seed to be distributed across the period and nature of transaction (cash/credit) to be followed in seed supply) on advance booking of seeds for coming season. SCF information was integrated with the DSSAT crop simulation model for risk assessment as well as to identify management options.