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Long Memory, Time Trends, and the Degree of Persistence in Water Temperatures of Five European Rivers and Lakes.

Authors :
Gil-Alana, Luis A.
Jesús González-Blanch, María
Lafuente, Carmen
Nõges, Tiina
Pulkkanen, Merja
Source :
Journal of Water Management Modeling; 10/18/2023, p1-22, 22p
Publication Year :
2023

Abstract

This paper uses long memory and fractional integration techniques to analyze the presence of time trends in the water temperatures of three large European rivers (the Rhine at Lobith, the Danube at Wienna, the Meuse at Eijsden) and two lakes (Saimaa in Finland, and Võrtsjäry in Estonia). Long memory is a feature frequently observed in hydrological data, and it is important to consider it to appropriately estimate the potential trends in the data. The results indicate the existence of significant positive trends in all the five series examined, possibly as a consequence of global warming. Interestingly, once the time trends are taken into consideration, the degree of persistence substantially decreases in all cases and the long memory property in the data disappears. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22926062
Database :
Complementary Index
Journal :
Journal of Water Management Modeling
Publication Type :
Academic Journal
Accession number :
173078484
Full Text :
https://doi.org/10.14796/JWMM.C505