Please use this identifier to cite or link to this item: https://idr.nitk.ac.in/jspui/handle/123456789/11053
Title: Evaluating the Performance of CHIRPS Satellite Rainfall Data for Streamflow Forecasting
Authors: Sulugodu, B.
Deka, P.C.
Issue Date: 2019
Citation: Water Resources Management, 2019, Vol.33, 11, pp.3913-3927
Abstract: Streamflow forecasting can offer valuable information for optimal management of water resources, flood mitigation, and drought warning. This research aims in evaluating the effectiveness of CHIRPS satellite rainfall data in comparison with IMD gridded Rainfall Data and development of various flow forecasting models. Daily rainfall data for three decades (1983 2012) over the Nethravathi Basin, Karnataka, India is used for analysis. The analysis is carried out for the monsoon season (June September), out of which 70% data considered for training the model and remaining for testing. Different input combinations are developed, and soft-computing methods like ANFIS, GRNN, PSO-ANN, and ELM are applied for flow forecasting on a temporal scale. The model performance is evaluated using various statistical indices like NNSE, RRMSE, and MAE. The results indicate that CHIRPS rainfall showed better performance in comparison with IMD data. ELM expressed an enhanced effect when compared to all other methods. The usefulness and effectiveness of CHIRPS data compared to IMD data has been explored. 2019, Springer Nature B.V.
URI: http://idr.nitk.ac.in/jspui/handle/123456789/11053
Appears in Collections:1. Journal Articles

Files in This Item:
File Description SizeFormat 
7 Evaluating the Performance of CHIRPS.pdf3.27 MBAdobe PDFThumbnail
View/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.