Long term evaporation pan data to estimate potential evaporation during the warm season on the Alaskan North Slope: Imnavait Creek basin

Thesis (M.S.) University of Alaska Fairbanks, 2017 Evapotranspiration plays a significant role in the hydrologic cycle of all basins, yet is only ccasionally measured in the Arctic. One simple index method to evaluate evapotranspiration is the evaporation pan. The energy environment surrounding the...

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Bibliographic Details
Main Author: Mumm, John Paul
Other Authors: Kane, Douglas L., Toniolo, Horacio, Schnabel, William
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://hdl.handle.net/11122/8134
Description
Summary:Thesis (M.S.) University of Alaska Fairbanks, 2017 Evapotranspiration plays a significant role in the hydrologic cycle of all basins, yet is only ccasionally measured in the Arctic. One simple index method to evaluate evapotranspiration is the evaporation pan. The energy environment surrounding the simple evaporation pan varies considerably from that of the natural environment. Yet, an evaporation pan is a sound way to determine and estimate the potential evapotranspiration, and actual evapotranspiration can be estimated from evaporation pan data by determining and employing a pan coefficient. An evaporation pan was initially installed in 1986 in the northern foothills of the Brooks Range on the North Slope of Alaska in Imnavait Creek Basin, collecting data for 22 years. The total summer maximum, average, minimum and standard deviation of pan evaporation were 34.9 cm, 29.9 cm, 19.7 cm and 9.3 cm, respectively from 1986 to 2008 (1989 missing). Both, the seasonal water balance and the Priestley-Taylor method for the 2.2 km² Imnavait Creek catchment were used to produce seasonal estimates of actual evapotranspiration. When used in conjunction with the evaporation pan measurements, an average pan coefficient of 0.58 was found in both cases, which was very similar to what was found in an earlier study on Imnavait Creek Basin. The evaporation pan results can also be correlated effectively with other measured variables (such as thawing degree days, air temperature, net radiation, vapor pressure deficit, precipitation, wind speed, and wind direction); this is a method that allows one to predict potential evapotranspiration in areas where it is not measured at broader spatial scales.