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.
Keywords: Filling gaps; Lake Peipsi; Lake water quality assessment; Monitoring; Transboundary.
© 2022 The Authors.