Evidence map›Paper›PMID 35958273›Full record

ArticleJournal of Great Lakes research2022

Opportunities for combining data of Estonian and Russian monitoring to reflect on water quality in large transboundary Lake Peipsi.

Olga Tammeorg, Lea Tuvikene, Sergey Kondratyev, Sergey Golosov, Ilya Zverev, Olga Zadonskaya, Peeter Nõges

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Article in Journal of Great Lakes research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Olga TammeorgChair of Hydrobiology and Fisheries, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia.
Lea TuvikeneChair of Hydrobiology and Fisheries, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia.
Sergey KondratyevInstitute of Limnology, Russian Academy of Sciences, ul. Sevast'yanova 9, St. Petersburg 199105, Russia.
Sergey GolosovInstitute of Limnology, Russian Academy of Sciences, ul. Sevast'yanova 9, St. Petersburg 199105, Russia.
Ilya ZverevInstitute of Limnology, Russian Academy of Sciences, ul. Sevast'yanova 9, St. Petersburg 199105, Russia.
Olga ZadonskayaState Hydrological Institute, 23, 2-ia liniia V.O., St. Petersburg 199053, Russia.
Peeter NõgesChair of Hydrobiology and Fisheries, Estonian University of Life Sciences, Kreutzwaldi 5, 51006 Tartu, Estonia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lake Peipsi, one of the world's largest lakes, is shared between Estonia and Russia. The water quality in different parts of the lake has so far been assessed independently. Here we explore opportunities for combining data of Estonian and Russian monitoring. For that, we 1) analysed the compatibility of data for some water quality variables; 2) estimated the potential effects of the differences in sampling frequency; 3) provided a few regression models to calculate the missing data for months not sampled by the Russian side. Data of the concurrent Estonian and Russian sampling indicated a good compatibility. Estonian data analysis suggested that water quality assessment results are sensitive to sampling frequency. For example, total phosphorus (TP) in the largest basin showed a long-term decreasing trend in three month data that disappeared when data for other months were added. Disregarding some months may lead to under- or overestimation of certain factors with no consistency in the response of different basins. Hence, data of the whole ice-free period are recommended for an adequate water quality assessment. Furthermore, we demonstrated that monthly values of the water quality variables of the same year are autocorrelated. Based on this, we filled the gaps in the long-term data and compiled a dataset for the whole lake that enables its most comprehensive use in water quality assessment and management. Long-term data revealed no water quality improvement of Lake Peipsi. Further reduction of the external nutrient load is needed. Eutrophication is sustained by high internal phosphorus load.

Indexed as

Filling gapsLake PeipsiLake water quality assessmentMonitoringTransboundary

Identifiers

PMID35958273
PMCPMC9353880

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.