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An energy balance approach to determine regional evapotranspiration based on planetary boundary layer similarity theory and regularly recorded data
Author(s) -
Abdulmumin S.,
Myrup Leonard O.,
Hatfield Jerry L.
Publication year - 1987
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 - 10.1029/wr023i011p02050
Subject(s) - evapotranspiration , sensible heat , energy balance , radiosonde , environmental science , boundary layer , latent heat , planetary boundary layer , water balance , similarity (geometry) , meteorology , atmospheric sciences , mathematics , turbulence , geology , geography , physics , mechanics , ecology , geotechnical engineering , artificial intelligence , computer science , image (mathematics) , biology , thermodynamics
An energy balance procedure was developed to determine regional evapotranspiration using only regularly recorded solar radiation and rawinsonde data. The major input terms in the basic energy balance equation are daily surface net radiation and sensible heat flux. Net radiation was determined by empirical and semiempirical radiation balance equations and the sensible heat flux term from an aerodynamic mass transfer equation derived from concepts of planetary boundary layer similarity theory. The procedure gave better results for a small (100 ha) agricultural watersheds than a comparable procedure based on purely aerodynamic mass transfer considerations, especially on 1‐ and 2‐day periods. For a larger (1000 ha) hydrologic watershed the model achieved acceptable accuracy for monthly estimates of regional evapotranspiration. On this time scale, comparison with observation yielded slopes from 0.97 to 1.14 with correlations between 0.90 and 0.91. For the monthly comparison, the purely aerodynamical model achieved virtually the same accuracy. These results were obtained using the same data set that was used to calibrate the model. When independent data were used, the accuracy for the monthly estimate degraded (slope 0.75, correlation 0.40). For bimonthly estimates, accuracy improved (slope 0.92, correlation 0.73).