Prediction of effective rainfall and crop water needs using data mining techniques

Abstract

The effective rainfall received plays a huge role in the growth of crops in agriculture during all stages of crop growth. There may be times when the effective rainfall received may not be enough to support crop growth and thus knowledge about it beforehand can help farmers in estimating the amount of water that has to be supplied through irrigation. Prediction of effective rainfall and crop water needs is a very challenging task which requires meticulous and scrupulous analysis of a profound list of factors such as temperature and humidity. In the past effective rainfall has been computed by taking three major factors into consideration, the humidity, temperature and the received rainfall. Many mathematical models have been proposed over the ages and many of them are still applied to find the effective rainfall. Here the effective rainfall is computed by performing a series of complex mathematical computations which have been broken up into simpler steps and given as an estimated figure. Important factors such as land evaporation transpiration rates, humidity, groundwater characteristics, and temperature have been considered to ascertain the effective amount of rainfall received in a designated area in a simpler way. This technique can be used to predict the amount of effective rainfall and in turn can also be used to predict the crop water needs for any particular area. For now this method is applied to determine the effective rainfall and crop water needs in Bijapur district of Karnataka to maximize crop yield and to avoid problems such as over irrigation of crops in that area.