Evaluating the performance of CHIRPS and CPC precipitation data for streamflow forecasting using multiple linear regression and Long Short-Term Memory Neural Network model

Evaluating the performance of CHIRPS and CPC precipitation data for streamflow forecasting using multiple linear regression and Long Short-Term Memory Neural Network model

Accurate streamflow forecasting is essential for effective water resources management and planning. Traditionally, streamflow prediction has relied heavily on a large volume of precipitation data from ground-based weather stations, which are often expensive to build and maintain and provide rainfall...

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Bibliographic Details
Main Authors: Khairul Hasan, Md Sahidul Islam, Khayrun Nahar Mitu, Mahade Ibn Salam, Nazli Aghashahi
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:MethodsX
Subjects:
Machine learning approach for streamflow forecasting using gauge-based and satellite-based rainfall data
Online Access:http://www.sciencedirect.com/science/article/pii/S2215016125002894
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