EVALUATION OF THE ENERGY BUDGET METHOD OF DETERMINING EVAPORATION AT WILLIAMS-LAKE, MINNESOTA, USING ALTERNATIVE INSTRUMENTATION AND STUDY APPROACHES

Citation
Do. Rosenberry et al., EVALUATION OF THE ENERGY BUDGET METHOD OF DETERMINING EVAPORATION AT WILLIAMS-LAKE, MINNESOTA, USING ALTERNATIVE INSTRUMENTATION AND STUDY APPROACHES, Water resources research, 29(8), 1993, pp. 2473-2483
Citations number
31
Categorie Soggetti
Limnology,"Environmental Sciences","Water Resources
Journal title
ISSN journal
00431397
Volume
29
Issue
8
Year of publication
1993
Pages
2473 - 2483
Database
ISI
SICI code
0043-1397(1993)29:8<2473:EOTEBM>2.0.ZU;2-F
Abstract
Best estimates of evaporation at Williams Lake, north central Minnesot a, were determined by the energy budget method using optimum sensors a nd optimum placement of sensors. These best estimates are compared wit h estimates derived from using substitute data to determine the effect of using less accurate sensors, simpler methods, or remotely measured data. Calculations were made for approximately biweekly periods durin g five open water seasons. For most of the data substitutions that aff ected the Bowen ratio, new values of evaporation differed little from best estimates. The three data substitution methods that caused the la rgest deviations from the best evaporation estimates were (1) using ch anges in the daily average surface water temperature as an indicator o f the lake heat storage term, (2) using shortwave radiation, air tempe rature, and atmospheric vapor pressure data from a site 110 km away, a nd (3) using an analog surface water temperature probe. Recalculations based on these data substitutions resulted in differences from the be st estimates as much as 89%, 21%, and 10%, respectively. The data subs titution method that provided evaporation values that most closely mat ched the best estimates was measurement of the lake heat storage term at one location in the lake, rather than at 16 locations. Evaporation values resulting from this substitution method usually were within 2% of the best estimates.