Evaluating the potential of rainfall product from Indian geostationary satellite for operational agromet advisory services in India

Abstract

Satellite remote sensing technology is increasingly gaining recognition as an important source of operational agro meteorological services. Spatial daily rainfall product from geostationary satellite is one of the important data source for quick evaluation of suitability of sowing conditions and other economically relevant agricultural operations (irrigation, fertilizer applications, spraying etc.) by farmers as well as disaster (drought, flood) warning causing crop loss and also to derive weather derivatives for crop insurance. In view of that a study was taken up to explore the use of satellite based rainfall data at different temporal scales. Under the present study, comparison has been made between Kalpana-1 high resolution (0.25° x 0.25°) rainfall estimates for four south-west monsoon months (June-September) in two contrasting monsoon periods of 2008 (normal) and 2009 (drought) with in situ measurements andforecast (1° x 1°) at nine AMFUs (Agro-Meteorological Field Units) in different agro climatic zones.Initial analysis show less correlation and large root mean square error (RMSE) of Kalpana-1 daily rainfall estimates with measurements and forecast. However, correlation was found to increase significantly from 60 to 80% over weekly to fortnightly scale with concomitant decrease in RMSE.