The working group on risk management in



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wg11 risk
3.3.2. Climate Prediction: Contingency crop plan strategies have been evolved through research efforts since the mid s, to minimize crop losses in the wake of aberrant weather conditions. Our experience in 2002, strikingly reveals that one of the major constraints in implementing contingency crop planning, is the lack of advance weather information during the kharif season, with reasonable lead-time and sufficient specificity,
to enable farmers to modify their decisions before and during the cropping season. The break and active cycles of monsoon like the one experienced in 2002, affect farming operations in varying degrees almost every year in one part of the country or the other.
This is of great significance, when we realise that 20-30% of the districts, suffer from deficient scanty rainfall, even in so called normal monsoon years.
Spatially and temporally differentiated weather information with a lead-time of days, could be of value to policy planners and farmer service organizations, to provide critical agriculture input support services to farmers. For example, a forecast of the July monsoon break, made and disseminated to the agricultural community 25 days before the event, could have significantly minimized damage to agriculture during the


23 2002 monsoon season. Assuming that a prediction on the dry spell likelihood of July, was available by the first or second week of June 2002, farmers could have been motivated to postpone agricultural operations saving investments. Water resource managers, could have introduced water budgeting measures. Similarly, the prediction of the revival of the monsoon in August 2002, could have motivated farmers, to undertake contingency crop-planning during pre-rabi season.
The Department of Agriculture and Cooperation, has undertaken a commendable project on Extended Weather Prediction for Agriculture Risk Management, in collaboration with the Indian Institute of Technology (IIT), India Meteorological Department (IMD) and
National Centre for Medium Range Weather Forecasting (NCMRWF), and other participating institutes. Substantial further progress is required, to enhance the capacity of the forecast institutions to provide downscaled prediction products with sufficient spatial and temporal resolution, to enable local level resource managers such as farmers, to make use of weather information for decision making purposes.

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