{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T21:54:09Z","timestamp":1781560449030,"version":"3.54.5"},"reference-count":23,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:00:00Z","timestamp":1781222400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Environmental Modelling & Software"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.envsoft.2026.107074","type":"journal-article","created":{"date-parts":[[2026,6,12]],"date-time":"2026-06-12T00:26:38Z","timestamp":1781223998000},"page":"107074","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Anomaly detection using continuous wavelet transforms and local active information storage scores: An application to water distribution networks"],"prefix":"10.1016","volume":"204","author":[{"ORCID":"https:\/\/orcid.org\/0009-0009-5657-6512","authenticated-orcid":false,"given":"Elvio","family":"Damonti","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giancarlo","family":"Bernasconi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"103","key":"10.1016\/j.envsoft.2026.107074_bib1","doi-asserted-by":"crossref","first-page":"7104","DOI":"10.21105\/joss.07104","article-title":"EPyT-Flow: a toolkit for generating water DistributionNetwork data","volume":"9","author":"Artelt","year":"2024","journal-title":"J. Open Source Softw."},{"key":"10.1016\/j.envsoft.2026.107074_bib2","series-title":"Leak Detection in Water Distribution Networks Using Gated Recurrent Neural Networks","author":"Bjerke","year":"2019"},{"issue":"1","key":"10.1016\/j.envsoft.2026.107074_bib3","doi-asserted-by":"crossref","first-page":"136","DOI":"10.2166\/hydro.2015.021","article-title":"Robust sensor placement for leak location: analysis and design","volume":"18","author":"Blesa","year":"2016","journal-title":"J. Hydroinform."},{"key":"10.1016\/j.envsoft.2026.107074_bib4","article-title":"Anomaly Detection in univariate time-series: a survey on the State-of-the-Art (Version 1)","author":"Braei","year":"2020","journal-title":"arXiv"},{"key":"10.1016\/j.envsoft.2026.107074_bib5","series-title":"Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data","first-page":"93","article-title":"LOF: identifying density-based local outliers","author":"Breunig","year":"2000"},{"key":"10.1016\/j.envsoft.2026.107074_bib6","author":"Burnaev"},{"key":"10.1016\/j.envsoft.2026.107074_bib7","author":"Chalapathy"},{"issue":"1","key":"10.1016\/j.envsoft.2026.107074_bib8","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1007\/s11269-025-04403-3","article-title":"An efficient data-driven leak detection strategy by enhancing a convolutional neural network approach using a Gaussian process regressor","volume":"40","author":"Damonti","year":"2026","journal-title":"Water Resour. Manag."},{"key":"10.1016\/j.envsoft.2026.107074_bib9","doi-asserted-by":"crossref","DOI":"10.1016\/j.dsp.2025.105603","article-title":"Moving forward in water distribution network leak identification through an innovative features engineering step","volume":"168","author":"Damonti","year":"2026","journal-title":"Digit. Signal Process."},{"key":"10.1016\/j.envsoft.2026.107074_bib10","series-title":"Ten Lectures on Wavelets (9. Print)","author":"Daubechies","year":"2006"},{"key":"10.1016\/j.envsoft.2026.107074_bib11","author":"Ishimtsev"},{"key":"10.1016\/j.envsoft.2026.107074_bib13","author":"Kyriakou"},{"issue":"92","key":"10.1016\/j.envsoft.2026.107074_bib14","doi-asserted-by":"crossref","first-page":"5947","DOI":"10.21105\/joss.05947","article-title":"EPyT: an EPANET-Python toolkit for smart water NetworkSimulations","volume":"8","author":"Kyriakou","year":"2023","journal-title":"J. Open Source Softw."},{"key":"10.1016\/j.envsoft.2026.107074_bib15","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111002","article-title":"A novel unsupervised framework for time series data anomaly detection via spectrum decomposition","volume":"280","author":"Lei","year":"2023","journal-title":"Knowl. Base Syst."},{"key":"10.1016\/j.envsoft.2026.107074_bib16","series-title":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1","article-title":"Water leak detection and localization using convolutional autoencoders","author":"Leonzio","year":"2023"},{"key":"10.1016\/j.envsoft.2026.107074_bib17","doi-asserted-by":"crossref","DOI":"10.1016\/j.asoc.2020.106919","article-title":"Clustering-based anomaly detection in multivariate time series data","volume":"100","author":"Li","year":"2021","journal-title":"Appl. Soft Comput."},{"key":"10.1016\/j.envsoft.2026.107074_bib18","author":"Li"},{"key":"10.1016\/j.envsoft.2026.107074_bib19","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.ins.2012.04.016","article-title":"Local measures of information storage in complex distributed computation","volume":"208","author":"Lizier","year":"2012","journal-title":"Inf. Sci."},{"issue":"2","key":"10.1016\/j.envsoft.2026.107074_bib20","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1190\/1.1441329","article-title":"Wave propagation and sampling theory\u2014Part II: sampling theory and complex waves","volume":"47","author":"Morlet","year":"1982","journal-title":"Geophysics"},{"issue":"9","key":"10.1016\/j.envsoft.2026.107074_bib21","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.14778\/3538598.3538602","article-title":"Anomaly detection in time series: a comprehensive evaluation","volume":"15","author":"Schmidl","year":"2022","journal-title":"Proceedings of the VLDB Endowment"},{"key":"10.1016\/j.envsoft.2026.107074_bib22","series-title":"WDSA\/CCWI Joint Conference","article-title":"LeakDB: a benchmark dataset for leakage diagnosis in water distribution networks","author":"Vrachimis","year":"2018"},{"key":"10.1016\/j.envsoft.2026.107074_bib24","series-title":"2024 8th International Conference on Electrical, Mechanical and Computer Engineering (ICEMCE)","first-page":"348","article-title":"An anomaly detection method based on continuous wavelet transform and deep convolutional generative adversarial network that only requires normal sample training","author":"Wang","year":"2024"},{"issue":"9","key":"10.1016\/j.envsoft.2026.107074_bib23","doi-asserted-by":"crossref","first-page":"5525","DOI":"10.3390\/app13095525","article-title":"Anomaly detection for automated vehicles integrating continuous wavelet transform and convolutional neural network","volume":"13","author":"Wang","year":"2023","journal-title":"Appl. Sci."}],"container-title":["Environmental Modelling & Software"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226002215?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1364815226002215?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,6,15]],"date-time":"2026-06-15T21:22:38Z","timestamp":1781558558000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1364815226002215"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":23,"alternative-id":["S1364815226002215"],"URL":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.107074","relation":{},"ISSN":["1364-8152"],"issn-type":[{"value":"1364-8152","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Anomaly detection using continuous wavelet transforms and local active information storage scores: An application to water distribution networks","name":"articletitle","label":"Article Title"},{"value":"Environmental Modelling & Software","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.envsoft.2026.107074","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Authors. Published by Elsevier Ltd.","name":"copyright","label":"Copyright"}],"article-number":"107074"}}