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16 - Soft Computing Methods and Water Management

from Part III - Sustainable Water Management under Future Uncertainty

Published online by Cambridge University Press:  17 March 2022

By
Mohammad Zounemat-Kermani  and
Meysam Alizamir
Edited by
Qiuhong Tang  and
Guoyong Leng
Qiuhong Tang
Affiliation:
Chinese Academy of Sciences, Beijing
Guoyong Leng
Affiliation:
Oxford University Centre for the Environment
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Summary

This chapter reviews recent developments in modern soft computing models, including heuristic algorithms, extreme learning machines and models based on deep learning strategies applied to water management. In this context, we describe the basics and fundamentals of the mentioned soft computing methods. We then provide a brief review of the models applied in three fields of water management: drought forecasting, evapotranspiration modelling and rainfall-runoff simulation. Thus, we provide guidelines for modern soft computing techniques applied to water management.

Keywords

HydrologyHydrometeorologyWater resourcesHydroinformaticsHydrosciencesMachine learningData miningDeep learning
Type
Chapter
Information
Climate Risk and Sustainable Water Management , pp. 342 - 373
Publisher: Cambridge University Press
Print publication year: 2022

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