Analysis of the Ecological State of Rivers of the Ararat Water Basin Management Area Using Background Concentrations

Abstract The article argues that an inherent limitation of maximum permissible concentrations is their inability consider the specificities of the geographical areas. In this regard, the Water Framework Directive developed by the European Union has played an important role in shifting river water quality assessment in Armenia from assessing maximum permissible concentrations of hydrochemical parameters to a more comprehensive approach which based on natural background concentrations. This shift, in force since 2011, emphasizes the importance of ecological integrity and use of natural reference points at the rivers for water quality assessment. The Decree of the Government of the Republic of Armenia “On Establishing Water Quality Standards for Each Basin Authority” distinguishes five separate classes and the assessment of chemical water quality is based on the class with the least favourable quality indicator. Water quality classes of the Vedi, Arpa and Yeghegis rivers for the period 2013–2024 were studied based on the analysis of background concentrations. The analysis showed that in a river waters under study the background concentrations of suspended solids, chemical oxygen demand, ammonium, nitrite and phosphate ions, as well as the following metals: manganese, molybdenum, aluminum, iron, barium and tin are exceeded.

Institutions

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-09-16
DOI
https://doi.org/10.5281/zenodo.17263921
Primary Topic
Agriculture, Water, and Health
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of the Ecological State of Rivers of the Ararat Water Basin Management Area Using Background Concentrations

Zenodo (CERN European Organization for Nuclear Research)
Agriculture, Water, and Health
article

Analysis of the Ecological State of Rivers of the Ararat Water Basin Management Area Using Background Concentrations

article en

Abstract

Abstract The article argues that an inherent limitation of maximum permissible concentrations is their inability consider the specificities of the geographical areas. In this regard, the Water Framework Directive developed by the European Union has played an important role in shifting river water quality assessment in Armenia from assessing maximum permissible concentrations of hydrochemical parameters to a more comprehensive approach which based on natural background concentrations. This shift, in force since 2011, emphasizes the importance of ecological integrity and use of natural reference points at the rivers for water quality assessment. The Decree of the Government of the Republic of Armenia “On Establishing Water Quality Standards for Each Basin Authority” distinguishes five separate classes and the assessment of chemical water quality is based on the class with the least favourable quality indicator. Water quality classes of the Vedi, Arpa and Yeghegis rivers for the period 2013–2024 were studied based on the analysis of background concentrations. The analysis showed that in a river waters under study the background concentrations of suspended solids, chemical oxygen demand, ammonium, nitrite and phosphate ions, as well as the following metals: manganese, molybdenum, aluminum, iron, barium and tin are exceeded.

Zenodo (CERN European Organization for Nuclear Research)
Yerevan State University (AM)
Clean water and sanitation
Openalex Percentile: Top 46%
Agriculture, Water, and Health
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.