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Seasonal evaporation cycle in oxbow lakes formed along the Tisza River in Hungary for flood control
Author(s) -
Babka Beáta,
Futó István,
Szabó Szilárd
Publication year - 2018
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13126
Subject(s) - hydrology (agriculture) , floodplain , environmental science , precipitation , evaporation , flood myth , stable isotope ratio , seasonality , groundwater , geology , ecology , geography , physics , geotechnical engineering , archaeology , quantum mechanics , meteorology , biology
As a result of water regulation, dykes (i.e., embankments against floods) were constructed along the Tisza River and meanders were cut to control the floods in the region. These cut‐off meanders resulted in oxbow lakes that are important locations for nature conservation. We collected water samples over 5 years in 7 campaigns to measure the δ 18 O (‰) and δ 2 H (‰) ratios in 45 oxbow lakes from the Upper Tisza Region (NE‐Hungary). We applied Random Forest Regression involving climatic data to reveal the connection with the stable isotopes. We determined that isotope ratios changed as a function of time, due to evaporation and a varying water supply (precipitation and groundwater). The average difference in the isotopic ratios for the river and oxbows increased from spring to winter, but decreased between the oxbows on both sides of the dyke. We found that isotope ratios were determined by the maximum monthly temperature in the case of oxbows in the active floodplain, whereas in case of oxbows on the reclaimed side, this was also influenced by the maximum monthly temperature, and the cumulative evaporation. As direct measurement of evaporation is difficult to evaluate, stable isotope measurements provided an effective quantitative alternative to estimate evaporation. Measuring the seasonality of the δ 18 O and δ 2 H is important to interpret the results and these data are useful to water management experts to identify the lakes at risk of running dry.