Predicting Standardized Streamflow index for hydrological drought using machine learning models

Predicting Standardized Streamflow index for hydrological drought using machine learning models

Hydrological droughts are characterized based on their duration, severity, and magnitude. Among the most critical factors, precipitation, evapotranspiration, and runoff  are essential in modeling the droughts. In this study, three indices of drought, i.e., Standardized Precipitation Index (SPI), Sta...

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Bibliographic Details
Main Authors: Shahabbodin Shamshirband, Sajjad Hashemi, Hana Salimi, Saeed Samadianfard, Esmaeil Asadi, Sadra Shadkani, Katayoun Kargar, Amir Mosavi, Narjes Nabipour, Kwok-Wing Chau
Format: Article
Language:English
Published: Taylor & Francis Group 2020-01-01
Series:Engineering Applications of Computational Fluid Mechanics
Subjects:
gene expression programming
hydrological drought
m5 model tree
machine learning models
standardized streamflow index
support vector regression
Online Access:http://dx.doi.org/10.1080/19942060.2020.1715844

Internet

http://dx.doi.org/10.1080/19942060.2020.1715844

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