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Estimation of land surface evaporation using a generalized nonlinear complementary relationship
Author(s) -
Zhang Lu,
Cheng Lei,
Brutsaert Wilfried
Publication year - 2017
Publication title -
journal of geophysical research: atmospheres
Language(s) - English
Resource type - Journals
eISSN - 2169-8996
pISSN - 2169-897X
DOI - 10.1002/2016jd025936
Subject(s) - evaporation , potential evaporation , environmental science , flux (metallurgy) , nonlinear system , water cycle , vegetation (pathology) , pan evaporation , calibration , water resources , meteorology , hydrology (agriculture) , mathematics , statistics , materials science , geology , geography , physics , medicine , ecology , pathology , quantum mechanics , metallurgy , biology , geotechnical engineering
Evaporation is a key component of the hydrological cycle and affects regional water resources. Although the physics of evaporation is well understood, its estimation in practice remains a challenge. Among available methods for estimating it, the complementary principle of Bouchet has the potential to provide a practical tool for regional water resources assessment. In this study, the generalized nonlinear formulation of this principle by Brutsaert (2015) was tested against evaporation measurements from four flux stations in Australia under different climatic and vegetation conditions. The method was implemented using meteorological data and Class A pan evaporation measurements. After calibration the estimated daily evaporation values were in good agreement with flux station measurements with a mean correlation coefficient of 0.83 and a bias of 4% on average. More accurate estimates of daily evaporation were obtained when the evaporative demand or apparent potential evaporation was determined from the Penman equation instead of from pan evaporation. The obtained parameter values were found to lie well within the ranges of reported values in the literature. Advantages of the method are that only routine meteorological data are required and that it can be used to estimate long‐term evaporation trends.