ABSTRACT
The spatially distributed rainfall datasets are the most appropriate input for distributed/semi-distributed hydrological model, and there is a less probability of uncertainty in this model. The output of rain gauge results in a high probability of uncertainty in models. The focus of the study is to check the feasibility of different rainfall datasets in hydrological modelling. In this current study, satellite-based four rainfall datasets are adopted. The available high resolution, Tropical Rainfall Measuring Mission (TRMM), and National Centers for Environmental Prediction (NCEP) analysis derived Climate Forecast System Reanalysis (CFSR), The Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) and Global Precipitation Climatology Centre (GPCP) rainfall datasets were used to evaluate the performance of the SWAT model. The performance evaluation of the SWAT model was checked with four rainfall datasets using the coefficient of determination (R2) and the coefficient of Nash-Sitcliff efficiency (NSE). It was found that TRMM, GPCP and APHRODITE rainfall datasets could be an alternative source, where APHRODITE is not suitable for the hydrological process because of weak %wet days. The rainfall data sets are used to forecast accurate surface runoff.
Acknowledgement
The author is thankful to NITT/MHRD for financially support extended to the PhD scholar (LS). This research was also possible with the use of publicly available datasets, including Landsat 8 provided by the United States Geological Survey (USGS), from their Website of https://earthexplorer.usgs.gov/, CPC temperature data provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their Web site at https://www.esrl.noaa.gov/psd/ and Precipitation data of TRMM provided by NASA Precipitation measurement mission (https://trmm.gsfc.nasa.gov/), APHRODITE downloaded fromthe Water Resources website of http://www.chikyu.ac.jp/, GPCP downloaded from the website of World Climate Research Programme and Global Energy and Water Cycle Experiment ftp://ftp.cgd.ucar.edu/archive/PRECIP/,CFSR from the website of National Centers for Environmental Prediction (NCEP) (https://rda.ucar.edu/),and streamflow data which was provided by Central water commission of India.
Disclosure statement
No potential conflict of interest was reported by the author(s).