Severe eutrophication of freshwater lakes, with the subsequent risk of algal blooms, has a critical effect on the safety of drinking water supplies in China and is one of the main environmental emergencies in the country. This paper focuses on Chao Lake, a large, shallow eutrophic lake used as a source of drinking water. The study considers the possibilities of improving the lake monitoring system and developing a SCADA system to manage the emergencies relating to water quality in order to meet the need of ensuring safe drinking water to the population of Chaohu City. The paper is presented in sub-sections that reflect the multitasking nature of the study, which focused on: (a) upgrading the monitoring system at lake and water treatment plant levels and also applying remote sensing, to develop a SCADA (Supervisory Control And Data Acquisition) system using neural networks to support prompt and effective management of emergency situations; (b) upgrading water collection and treatment technologies

Monitoring, environmental emergencies management and water treatment improvement of freshwater lakes in China: the Chao Lake case study

ANTONELLI, MANUELA;NURIZZO, COSTANTINO
2011-01-01

Abstract

Severe eutrophication of freshwater lakes, with the subsequent risk of algal blooms, has a critical effect on the safety of drinking water supplies in China and is one of the main environmental emergencies in the country. This paper focuses on Chao Lake, a large, shallow eutrophic lake used as a source of drinking water. The study considers the possibilities of improving the lake monitoring system and developing a SCADA system to manage the emergencies relating to water quality in order to meet the need of ensuring safe drinking water to the population of Chaohu City. The paper is presented in sub-sections that reflect the multitasking nature of the study, which focused on: (a) upgrading the monitoring system at lake and water treatment plant levels and also applying remote sensing, to develop a SCADA (Supervisory Control And Data Acquisition) system using neural networks to support prompt and effective management of emergency situations; (b) upgrading water collection and treatment technologies
2011
cyanobacteria bloom; drinking water treatment; early-warning system; eutrophication; neural networks; remote sensing
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/641727
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact