Estimating daily lake evaporation from biweekly energy‐budget data

Abstract

Estimates of daily lake evaporation based on energy‐budget data are poor because of large errors associated with quantifying change in lake heat storage over periods of less than about 10 days. Energy‐budget evaporation was determined during approximately biweekly periods at a northern Minnesota, USA, lake for 5 years. Various combinations of shortwave radiation, air temperature, wind speed, lake‐surface temperature, and vapour‐pressure difference were related to energy‐budget evaporation using linear‐regression models in an effort to determine daily evaporation without requiring the heat‐storage term. The model that combined the product of shortwave radiation and air temperature with the product of vapour‐pressure difference and wind speed provided the second best fit based on statistics but provided the best daily data based on comparisons with evaporation determined with the eddy‐covariance method. Best‐model daily values ranged from −0.6 to 7.1 mm/day over a 5‐year period. Daily averages of best‐model evaporation and eddy‐covariance evaporation were nearly identical for all 28 days of comparisons with a standard deviation of the differences between the two methods of 0.68 mm/day. Best‐model daily evaporation also was compared with two other evaporation models, Jensen–Haise and a mass‐transfer model. Best‐model daily values were substantially improved relative to Jensen–Haise and mass‐transfer values when daily values were summed over biweekly energy‐budget periods for comparison with energy‐budget results.

Insight into the stable isotopic composition of glacial lakes in a tropical alpine ecosystem: Chirripó, Costa Rica

“…The average smaller E/I ratio for Lake Chirripó compared with Lake Ditkevi and the Morrenas lakes appear to be related to the greater lake heat storage (Andreasen, Rosenberry, & Stannard, ) of Lake Chirripó, which has an area of 7.8 × 10 4 m 2 and a mean depth of 8.2 m (Göcke et al, ). The lake system located in Valle de las Morrenas, for example, has an area of ~1.2 × 10 5 m 2 , but a smaller mean depth of 5.2 m (Horn et al, ), which reduces the heat storage and enhances evaporation.…”

The Importance of Heat Storage for Estimating Lake Evaporation on Different Time Scales: Insights From a Large Shallow Subtropical Lake

“…For example, the lag time between LE and Rn is 1 month for Poyang Lake in China with an average depth of 2.9 m (Cui et al., 2021), 2–3 months for Qinghai Lake in China with an average depth of 21 m (Li et al., 2016), and 5 months for Lake Superior in North America with an average depth of 148 m (Blanken et al., 2011). Therefore, many studies have emphasized the importance of G c in estimating lake evaporation ( E w ) when using the energy balance‐based E w models (Andreasen et al., 2017; Gan & Liu, 2020b; Winter et al., 1995). Furthermore, the effect of G c on E w is highly dependent on the time scale considered.…”

Evaporation from boreal reservoirs: A comparison between eddy covariance observations and estimates relying on limited data

“…The vast majority of studies evaluating the performance of evaporation equations have relied on indirect measurements of the flux, such as evaporation pans installed over land or residual energy budget calculations (Andreasen et al, 2017; Delclaux et al, 2007; Rimmer et al, 2009; Warnaka & Pochop, 1988; Winter et al, 1995). Evaporation pans are widely recognized as being the least accurate measurement method, mainly due to a shallow water column that cannot replicate the heat storage of a lake (Tanny et al, 2008; Winter, 1981).…”