Rainfall plays an important role in agricultural production. It has a profound influence on the growth, development and yields of a crop, incidence of pests and diseases, water needs and fertilizer requirements in terms of differences in nutrient mobilization due to water stresses and timeliness and effectiveness of prophylactic and cultural operations on crops. Occurrences of erratic rainfall are beyond human control. However, it is possible to adapt to or mitigate the adverse effects if a forecast of the rainfall can be had in time. Accurate information on rainfall is essential for the planning and management of agricultural operations. Nevertheless, rainfall is one of the most complex and difficult elements of the hydrology cycle to understand and to model due to the complexity of the atmospheric processes that generate rainfall and the tremendous range of variation over a wide range of scales both in space and time. Thus, accurate rainfall forecasting is one of the greatest challenges in operational hydrology. An attempt has been made here to develop a Final Long range Forecast of seasonal monsoon based on multiple regression technique to predict monsoon rainfall based on 16 parameters related with Anand (Gujarat). The 16 parameter of Anand for the last 25 years (1980-2005) was used for development of model. The operational forecast was given by using mean of both the models which has less error, (Avg. Error 3.5% for MRM-I and 5.1% for MRM-II respectively). The operational forecast is having still less error i.e. 0.6% for all data (1980-2009) and 2.9% for independent data (2006 to 2009), so it can be used for giving final forecast.

 

Key words: Rainfall forecast, multiple regression techniques, rainfall analysis.