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Guest Editors:
Professor Guangtao Fu, University of Exeter
Dr Andrea Cominola, Technische Universität Berlin and Einstein Center Digital Future
Professor David J. Hill, Thompson Rivers University
In recent years, the immense potential of artificial intelligence (AI) has been widely recognised within both the water research community and the water industry, with a growing number of studies and AI-driven systems reported in the literature. This special collection is dedicated to presenting the latest advances in the development and application of AI-based approaches and computer systems to address intricate challenges in water resources management, such as, rainfall forecasting, reservoir operation, pressure control, and urban water infrastructure monitoring, operation, and maintenance. It provides an insight into the challenges and future research directions within the realm of integrating AI with water research, which is pivotal to build sustainable and resilient water systems of the future.
Papers in this Collection
Downscaling of Precipitation for Climate Change Projections Using Multiple Machine Learning Techniques: Case Study of Shenzhen City, China
Jing-Cheng Han; Wenting Zheng; Zhe Liu; Yang Zhou; Yuefei Huang; and Bing Li
Published online: September 10, 2022
Advanced Rule-Based System for Rainfall Occurrence Forecasting by Integrating Machine Learning Techniques
Vikas Kumar Vidyarthi; and
Ashu Jain
Published online: October 21, 2022
Adoption of Artificial Intelligence in Drinking Water Operations: A Survey of Progress in the United States
Alyson H. Rapp, S.M.ASCE; Annelise M. Capener, S.M.ASCE; and
Robert B. Sowby, Ph.D., M.ASCE
Published online: May 12, 2023
Comparative Effectiveness of Data Augmentation Using Traditional Approaches versus StyleGANs in Automated Sewer Defect Detection
Qianqian Zhou;
Zuxiang Situ; Shuai Teng; and Gongfa Chen
Published online: July 10, 2023
Balancing Losses of Multipurpose Reservoirs by an Integrated Knowledge-Based System
Mahdi Sedighkia; Shahrzad Kaviani; and Asghar Abdoli
Published online: July 21, 2023
Cloud-Based Artificial Intelligence Analytics to Assess Combined Sewer Overflow Performance
Will Shepherd, Ph.D.;
Stephen Mounce, Ph.D.; Gavin Sailor; John Gaffney, Ph.D.; Neeraj Shah; Nigel Smith; Adam Cartwright, Ph.D.; and Joby Boxall, Ph.D.
Published online: July 26, 2023
Leveraging Deep Reinforcement Learning for Water Distribution Systems with Large Action Spaces and Uncertainties: DRL-EPANET for Pressure Control
Anas Belfadil; David Modesto, Ph.D.;
Jordi Meseguer, Ph.D.; Bernat Joseph-Duran, Ph.D.; David Saporta; and Jose Antonio Martin Hernandez, Ph.D.
Published online: November 16, 2023