Use of advance geospatial tools for estimation of spatial rainfall

The rainfall is the basic input for the development, testing, operation and use of the hydrologic models. Since the rainfall measurement is discrete over the area, estimation of average rainfall that falls on the watershed during the storm is an important hydrological exercise. The spatial distribution of rainfall is affected by many factors. Rain-gauge networks are designed to sample this distribution optimally. A method of estimating mean aerial rainfall should be able to represent this distribution as the realistic spatial distribution will give better accuracy of the dependent parameters. Various methods for converting the point rainfall to areal rainfall are in vogue. Conventional methods used for computing the spatial rainfall do consider the actual rainfall spatial variability. However, using present computing capabilities, information from Satellite Remote Sensing (SRS) and GIS tools, it is feasible to compute the spatial rainfall based on the storm rainfall pattern more accurately. The spatial analysis of the rainfall event using geospatial tools-Digital Rainfall Modelling- is an innovative tool for better assessment of the spatial rainfall. In addition, to resolve the problems of incomplete rainfall data, probable rainfall data can be estimated through spatial techniques. This paper discusses digital rainfall model for the study area for estimation of spatial rainfall distribution. The results compared with the common conventional methods showed significant improvements. The peak storm events in the Panshet watershed near Pune [India] are used for the said analysis.