Data analysis in research

To prepare agriculture and forestry for adapting to meteorological risks, another challenge is that efforts must be made in research, based on the knowledge of climate data currently available, and orienting it towards the development of the most useful techniques, ttese developments must be accompanied by efforts in agronomic research which take the hypothesis related to climatic extremes and variability into account in research in plant genetic improvement and development of sustainable cropping systems to attain the delivery of operational applications regarding adaptation strategies. It then becomes indispensable to single out two types of adaptation depending on the final user: those which can be implemented by the farmer himself (modification of sowing dates, varietal choice, use of seasonal forecasts, etc.) and those for decision-makers, land and natural resource managers which necessitate investment in development and construction infrastructures.

The concept of the Markov Chain probability model (Robertson 1976) on initial and transitional probabilities of dry and wet spells has been found a very useful tool for crop planning and drought monitoring, tte Markov Chain model can be fitted to weekly rainfall totals to obtain sequences of dry and wet spells, ttese initial and transitional probabilities can be used for answering several questions concerning the expected frequencies of sequences of dry and wet weeks, tte challenge here is that understanding sequences of wet and dry spells should help in preparing better agro-advisories, which should help farmers and agricultural scientists to take appropriate decisions for farm operations (Biswas 1994).

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