Comparing Station Based and Gridded Rainfall Data for Hydrological Modelling

Abstract

In the domain of hydrological modelling precipitation is one of the essential parameter as an input variable. Precipitation input as point gauge based rainfall data is commonly to use in hydrological modelling. Point gauge based rainfall data measurement has a very big limitation of spatial coverage of rainfall data over the area. Most of the countries in the world has very poor density of rain gauge network including India. Catastrophic change in the climate condition made hydrological modelling less reliable when it comes to application of point gauge based rainfall. Thus, it is very important to use rainfall record which has a good spatial as well as temporal resolutions. Precipitation measurement has been significantly evolved after introduction of remote sensing technologies. There are very few method/model of satellite driven rainfall, which has very good spatio-temporal gridded resolution of rainfall records. This paper presents a comprehensive review of such multi-satellite precipitation estimates of gridded rainfall data set over the World. The data sets which we have selected has more than three decades of various precipitation data, i.e., Moderate Resolution Imaging Spectroradiometer (MODIS), PERSIANN-Cloud Classification System (PERSIANN-CCS), Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE’s), Climate Prediction Center (CPC), Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Climatology Project (GPCP). The application of satellite based rainfall measurement and its application in hydrological modelling also discussed in this paper, briefly.