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A novel method for estimating the onset of thermal stratification in lakes from surface water measurements
Author(s) -
Woolway R. Iestyn,
Maberly Stephen C.,
Jones Ian D.,
Feuchtmayr Heidrun
Publication year - 2014
Publication title -
water resources research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.863
H-Index - 217
eISSN - 1944-7973
pISSN - 0043-1397
DOI - 10.1002/2013wr014975
Subject(s) - diel vertical migration , stratification (seeds) , environmental science , surface water , thermal stratification , range (aeronautics) , root mean square , thermal , geology , atmospheric sciences , soil science , hydrology (agriculture) , climatology , meteorology , materials science , oceanography , thermocline , geography , geotechnical engineering , physics , quantum mechanics , composite material , seed dormancy , botany , germination , dormancy , environmental engineering , biology
High‐frequency surface water temperature measurements were analyzed for 17 annual data series from seven lakes to assess whether the onset of thermal stratification can be determined from time series of surface water temperature measurements alone. Current methods for estimating the start of thermal stratification require depth‐resolved temperature measurements, whereas many existing high‐frequency measurements are often limited only to the lake surface. In this study, we show that the magnitude of the diel surface water temperature range can be used to estimate the onset of thermal stratification. We assess the accuracy of using the diel range as an estimate of the onset of thermal stratification by applying two methods based on the calculation of (1) the absolute difference in the diel surface temperature range and (2) the magnitude of the diel range from wavelet analysis. Our study shows that the onset of thermal stratification can be accurately estimated by wavelet analysis with a root mean square error of 2.1 days and by the observed diel temperature range method with a root mean square error of 11.8 days. This approach enables existing, and future, high‐resolution surface water data sets to be used to estimate the onset of lake stratification. Furthermore, the continuously increasing observational powers of satellites may eventually result in surface water temperature being measured at a sufficiently high temporal resolution at the spatial scales of small lakes to allow the onset of thermal stratification to be estimated remotely.