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Audiovisual . 2024
License: CC BY
Data sources: Datacite
ZENODO
Audiovisual . 2024
License: CC BY
Data sources: Datacite
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Fourth SafecREW and H2OforAll Webinar - Drinking Water Systems Modelling and Digitalization

Authors: SafeCREW; H2OforAll; ZeroPollution4Water Cluster;

Fourth SafecREW and H2OforAll Webinar - Drinking Water Systems Modelling and Digitalization

Abstract

On 3 December 2024, H2OforAll and SafecREW conducted their fourth common webinar. More than 60 participants listened to the four presentations on “Drinking Water Systems Modelling and Digitalization” and engaged in the disscussion. Albert Nardi and Aitor Iraola, the invited speakers from Amphos21, talked about digital solutions for the water sector. They firstly showed their approach to assess risk and vulnerability for companies due to climate change by calculating hazards using climate prediction models. Then, they talked about the use of machine learning algorithms for water management, specifically for the prediction of river flooding when extreme rain events occurs (minutes 10:40-29:00). They were followed by Balaram Guddanti who presented H2OforAll DBP modelling results to enhance water quality monitoring (minutes 29:00-43:30). The third presentation of Laura Vinardell focused on estimation models for DBPs in drinking water distribution networks, applied to the SafeCREW case study in Tarragona (minutes 43:30-59:57). The final talk centred around hydraulic and quality modelling of water distribution networks. Telmo Paula and Nuno Simões presented the modelling approach for Águas de Coimbra, host of the H2OforAll case study (from 1:00:00 to 1:18:00). Agenda 15:00 Welcome 15:05 – 15:30 Digitalization tools for the water sectorAlbert Nardi and Ester Vilanova, Digital Solutions Department, Amphos 21, Barcelona (Minute 10:40) 15:30-15:45 Detection and modelling of disinfection by-products: Enhancing water quality monitoringMartijn Wagterveld (Wetsus) and Balaram Guddanti (University of Twente), H2OforAll-team (Minute 29:00) 15:45-16:00 Estimation models for DBPs in drinking water distribution networksLaura Vinardell Magre, researcher at Eurecat, SafeCREW-team (Minute 43:30) 16:00-16:15 Hydraulic and quality modelling of water distribution networks: Coimbra Case StudiesTelmo Paula (Águas de Coimbra) and Nuno Simões (University of Coimbra), H2OforAll-team (Hour 1:00:00) 16:15-16:30 Q&A and conclusions

Keywords

Water management, Machine learning, Drinking water, prediction models, hydraulic modelling, Water monitoring, drinking water distribution networks, digitalisation, DBP, Modelling, Risk assessment

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average