Battle of Water Demand Forecasting

As part of the Battle of Water Networks competition series, the Battle of Water Demand Forecasting (BWDF) was organized in the context of the 3rd Water Distribution Systems Analysis and Computing and Control in the Water Industry (WDSA-CCWI) joint conference held in Ferrara (Italy) in 2024. In line with the previous editions of the Battle of Water Networks—the main objective of which was to address a specific problem related to the design and operation of water distribution networks—the BWDF aims to compare the effectiveness of methods for the short-term forecast of urban water demand in a set of real district metered areas. During the conference, 31 teams across the world participated in the BWDF and presented their approaches. The results obtained demonstrate the importance of (1) considering integrated approaches for short-term water demand forecasting; and (2) evaluating their performance in relation to more than one metric, case study, and period.

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Publication Details

Journal
Journal of Water Resources Planning and Management
Published
2025-07-18
DOI
https://doi.org/10.1061/jwrmd5.wreng-6887
Citations
6
Primary Topic
Water resources management and optimization
Type
article
Field-Weighted Citation Impact
6.87
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article

Battle of Water Demand Forecasting

Andreas Wünsch, Marco Franchini, Salvatore Cuomo, Aliasger K. Salem et al.
6 citations
Journal of Water Resources Planning and Management
Water resources management and optimization
6.87
article

Battle of Water Demand Forecasting

Andreas Wünsch, Marco Franchini, Salvatore Cuomo, Aliasger K. Salem, Raquel Barreira, Dionysios Nikolopoulos, Valentina Marsili, Matthew Hayslep, Ulrich Dittmer, Maria Mercedes Gamboa-Medina, Alexander Sinske, Bing Hui Hou, Amin E. Bakhshipour, Valerie Vaquet, Δημήτριος Γ. Ηλιάδης, Luca Hermes, Jorge E. Pesantez, Sergio Cardona, Mulenga Kalumba, Morgan DiCarlo, Laura González, Christos Makropoulos, Liesel Hans, Enrico Creaco, Alireza Koochali, Nelson Carriço, Gilberto Reynoso-Meza, E. Alvarado, Aly-Joy Ulusoy, George Moraitis, Florian Ziel, Lindsay Basto, Mario Pagano, Carlo Giudicianni, Ahmed A. Abokifa, Andrea Menapace, Annalaura Gabriele, Christos Michalopoulos, Huizhe Cao, Minsoo Kang, Bruno Brentan, João Caetano, Yaniv Romano, Giovanni Francesco Santonastaso, Jonas Vaquet, Dragan A. Savic, Rong Shen, Steffen Wallner, Vincenzo Schiano Di Cola, Panagiotis Samartzis, Dennis Zanutto, Elad Salomons, Björn Sonnenschein, Bradley Jenks, Phoebe Koundouri, F. Javier Martínez-Solano, Filippo Mazzoni, Martin Oberascher, Raziyeh Farmani, Carlos Jara‐Arriagada, Siming Bayer, Fayzul Pasha, Christian Kühnert, Hyun-Joo Bae, Dehui Wang, Ivan Stoianov, Stefano Alvisi, Gal Perelman, Juan Guillermo Saldarriaga, Felipe Campos, T.K. Ko, K. Li, Alemtsehay G. Seyoum, Shuicai Wu, Arno de Klerk, Kwang‐Ju Kim, Mashor Housh, Mohammadali Geranmehr, M. S. Jahangir, Rudy Gargano, Jens Kley-Holsteg, Pedro L. Iglesias‐Rey, Robert Sitzenfrei, Ariele Zanfei, E. Todini, Gregor Johnen, Maria Grazia Quarta, Joaquín Izquierdo, Fabian Hinder, Victoria Rodríguez, A. Ramachandran, Lydia Tsiami, Ali Haghighi, Panagiotis Kossieris, Yuwei He, Kondwani Simukonda, Konstantinos Glynis, Emily Zechman Berglund, Ioannis Tsoukalas, Yao Yuan, Manuel Herrera, Juneseok Lee, Mathias Ziebarth, Hua Guo, John Quilty, Armando Di Nardo, Fei Gao, Georgios Alexandros Chatzistefanou, R. Dziedzic, Bruno Ferreira, Hossein Namdari, Lydia Vamvakeridou-Lyroudia, Alejandra Tabares, Marios M. Polycarpou, Claudia Quintiliani, Daniela Biondi, Avi Ostfeld, Barbara Hammer, Qidong Que, Niuosha Hedaiaty Marzouny, Faten Ayyash, Huan Liu, Wenyan Wu, Haiyang Zhang, Jie Yu, Yanmei Li, Andreas Maier, Jinliang Gao, Matthias Groß, Santiago Gómez, In‐Su Jang, Yuanyang Liu, Yesid Coy, Fatemeh Boloukasli ahmadgourabi, Juan Perafán, Mostapha Kalami Heris, Adam Kulaczkowski, Kristina Arsova, Dennis Schol, Alfredo Iglesias-Rey, Jiyan Zou, Melica Khashei Varnamkhasti, Morad Nosrati Habibi, Hebatullah Yehia Saad Mousa, Adrian van Heerden, C. A. López-Hojas
article en
6 citations

Abstract

As part of the Battle of Water Networks competition series, the Battle of Water Demand Forecasting (BWDF) was organized in the context of the 3rd Water Distribution Systems Analysis and Computing and Control in the Water Industry (WDSA-CCWI) joint conference held in Ferrara (Italy) in 2024. In line with the previous editions of the Battle of Water Networks—the main objective of which was to address a specific problem related to the design and operation of water distribution networks—the BWDF aims to compare the effectiveness of methods for the short-term forecast of urban water demand in a set of real district metered areas. During the conference, 31 teams across the world participated in the BWDF and presented their approaches. The results obtained demonstrate the importance of (1) considering integrated approaches for short-term water demand forecasting; and (2) evaluating their performance in relation to more than one metric, case study, and period.

Journal of Water Resources Planning and ManagementVol. 151(10)
TH Köln - University of Applied Sciences (DE), Universidade Federal de Minas Gerais (BR), SAS Institute (United States) (US), Birmingham City University (GB), American Association For The Advancement of Science (US), North Carolina State University (US), Electronics and Telecommunications Research Institute (KR), University of Salento (IT), Democritus University of Thrace (GR), University of Waterloo (CA), University of Kaiserslautern (DE), Free University of Bozen-Bolzano (IT), Technion – Israel Institute of Technology (IL), National Technical University of Athens (GR), Pontifícia Universidade Católica do Paraná (BR), Universidade de São Paulo (BR), University of Cologne (DE), Università degli studi di Cassino e del Lazio Meridionale (IT), Universität Innsbruck (AT), University of Macedonia (GR), Schiller International University (FR), Shahid Chamran University of Ahvaz (IR), Bielefeld University (DE), University of Ferrara (IT), Hochschule Bielefeld (DE), Harbin Institute of Technology (CN), Cyber University (JP), University of Exeter (GB), University of Pavia (IT), Dalian University of Technology (CN), German Research Centre for Artificial Intelligence (DE), University of Zambia (ZM), University of Cyprus (CY), Beijing University of Technology (CN), Universidade Politécnica de Setúbal (PT), Italian Society of Physiotherapy (IT), Fraunhofer Institute of Optronics, System Technologies and Image Exploitation (DE), RED Consulting (Norway) (NO), University of Campania "Luigi Vanvitelli" (IT), Observatorio de Prospectiva Tecnológica Industrial (ES), KWR Water Research Institute (NL), Universidad de Los Andes (BO), Concordia University (US), Sequoia (United States) (US), University of Calabria (IT), Imperial College London (GB), Universidade Federal do Paraná (BR), Manhattan University (US), Universitat Politècnica de València (ES), University of Duisburg-Essen (DE), California State University, Fresno (US), University of Naples Federico II (IT), Sheffield Hallam University (GB), University of Applied Sciences Kaiserslautern (DE), Athens University of Economics and Business (GR), University of Newcastle Australia (AU), Newcastle University (GB), University of Sheffield (GB), University of Haifa (IL), Politecnico di Milano (IT)
Openalex Percentile: Top 3%
Water resources management and optimization
6.87
DOIOpen Access PDFOpenAlex
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