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Sustainable Water Resources Management

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01.06.2020 | Original Article

Managing nutrient pollution in Venice Lagoon (Italy): a practical tool for assessment of water quality

verfasst von: S. Çevirgen, H. Elwany, M. Pesce, A. Zirino

Erschienen in: Sustainable Water Resources Management | Ausgabe 3/2020

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Abstract

Venice Lagoon is one of the most studied coastal lagoons in Europe. Although there are various modelling studies of the lagoon in the literature, it is hard to find a verified model of the whole lagoon that considers the chemical/biological properties of the lagoon from more than 2 years of time series data. In this study, we developed a steady-state model of Venice Lagoon that predicts the interactions among major variables against measurements made during a 9-year monitoring programme (MAV-CVN in Attivita’ di Monitoraggio Ambientale della Laguna di Venezia: MELa1-5, Attivita’ A.2: Trattamento ed analisis dei dati, elaborazione in linea, ed’ interpretazioni, 2000–2010) using AQUATOX, a U.S. EPA sponsored water quality model. The model includes 5 segments and shows the gradient of ecosystem properties of the lagoon, in accordance with the variant salinity and residence times. The lagoon’s trophic status was evaluated through TRIX Index. Application of the index revealed that Venice Lagoon needs to be restored by reducing nutrient loads. We further propose two management scenarios, which act on agricultural phosphorus and nitrogen loads originating within the Venice Lagoon Watershed. Scenario analysis shows that the Venice Lagoon trophic status can be improved from a poor to a moderate/good condition in the most impacted zone.

Vorheriger Artikel Water balance theory is more than 340 years old

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Titel: Managing nutrient pollution in Venice Lagoon (Italy): a practical tool for assessment of water quality
verfasst von: S. Çevirgen
H. Elwany
M. Pesce
A. Zirino
Publikationsdatum: 01.06.2020
Verlag: Springer International Publishing
Erschienen in: Sustainable Water Resources Management / Ausgabe 3/2020
Print ISSN: 2363-5037
Elektronische ISSN: 2363-5045
DOI: https://doi.org/10.1007/s40899-020-00390-y

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