DROUGHT PREDICTION FROM GENERAL CIRCULATION ATMOSPHERIC MODELS USING HYBRID DATA MINING TECHNIQUES.

The world has been developing with new creativity and technologies on the other hand the natural calamities are high and still rising all over the world. Among the different natural calamities, drought is a more complicated one. The main reason for the drought facing is due to ignorance of water management and not involved in taking remedial action to overcome the drought in many developing and developed countries. The drought will differ in different regions depending on the drought frequency, its duration to affect based on the changes in weather condition. In the developing world, the factor behind the increasing drought is an increase in population, changes in lifestyle and improved urbanization and the utilization of land to a larger extend by destroying trees and plants. Destruction in environmental conditions leads to an increase in temperature and causes severe drought within a short duration. The drought risk management is not an easy process to be carried by an individual as well as the government, a proper co-operation is required to overcome this consequence. Continuous monitoring and early warning system have to be promoted to face the critical situation in drought-affected areas. Continuous seasonal forecasting is considered to be a principle for risk management where the drought characteristics are considered for the investigation of risk management. Depending on the atmospheric models various techniques are developed for the proper monitoring of drought and other natural calamities. This invention proposed for the accurate prediction of data related to the drought and famine estimation due to the stimulating changes in the global climate and their causes. This invention is involved in monitoring and also provide a warning during severe drought conditions by using hybrid data mining techniques. The proposed invention is provided with a data mining algorithm mainly to enable a fast prediction to maintain the water balance in the drought-affected region.