Environmental Monitoring for Genomic Damage After an Environmental Accident in a River in the Brazilian Northeast

Silva, Demetrios Lucas da; Lima, Anderson Rodrigues Balbino de; Souza, José Rodolfo de Lima; Adam, Mônica Lúcia

doi:10.1007/s11270-022-05967-1

Water Air Soil Pollut

2022

DOI: 10.1007/s11270-022-05967-1

|View full text |Cite

Environmental Monitoring for Genomic Damage After an Environmental Accident in a River in the Brazilian Northeast

Demetrios Lucas da Silva

Anderson Rodrigues Balbino de Lima

José Rodolfo de Lima Souza

et al.

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article1

Relationship

Self Cite0

Independent1

Authors

Journals

Cited by 1 publication

References 40 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

Water quality emergency monitoring networks: A method for identifying non-critical variables based on Shannon's entropy

Cruz,

Silva

2024

Journal of Hydroinformatics

View full text Add to dashboard Cite

In the occurrence of environmental disasters involving water resources, deploying an emergency monitoring network for assessing water quality is within the first measures to be taken. Emergency networks usually cover a large set of water quality variables and monitoring stations along the watershed. Focusing on variables that represent greater risk to the environment and have less predictable spatial and temporal distribution is a strategy to optimize efforts on monitoring. The goal of this study is to assess the use of Shannon's entropy to identify non-critical water quality variables in an emergency monitoring network implemented in a watershed impacted by the collapse of a mining iron tailing dam, the Doce River watershed (Brazil). Monitoring stations were grouped into water quality subregions through cluster analysis and Shannon's entropy was used to estimate information redundancy of monitored variables. From information redundancy and after checking for compliance with environment normative, non-critical water quality variables were identified. Results indicated that non-critical variables represent 32–50% of the variables monitored. Emergency network managers find in this method a robust tool to improve the network performance. However, special attention should be paid to outliers' presence that can bias analyses based on Shannon's entropy.

show abstract

Water quality emergency monitoring networks: A method for identifying non-critical variables based on Shannon's entropy

Cruz,

Silva

2024

Journal of Hydroinformatics

View full text Add to dashboard Cite

show abstract

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Environmental Monitoring for Genomic Damage After an Environmental Accident in a River in the Brazilian Northeast

Cited by 1 publication

References 40 publications

Water quality emergency monitoring networks: A method for identifying non-critical variables based on Shannon's entropy

Water quality emergency monitoring networks: A method for identifying non-critical variables based on Shannon's entropy

Contact Info

Product

Resources

About