Article ID Journal Published Year Pages File Type
82121 Agricultural and Forest Meteorology 2011 10 Pages PDF
Abstract

Evapotranspiraton (ET) estimation based on scaling up from leaf stomatal conductance (gs) to canopy conductance (gc) is important in improving effective use and evaluation of agricultural water resources. Taking a summer maize field in north China as an example, after the response of gs to main environmental factors was analyzed based on the measured value, the Jarvis model for gs was established and calibrated. Then the weighted integration model (WI model) was established on the basis of weighted model (W model) after considering the difference of intercept diffuse radiation by shaded leaves in different canopy heights and nonlinear relationship between gs and the photosynthetically active radiation (PAR) to improve gc estimation for shaded leaves using integration equation. Meanwhile the estimation accuracy of W and WI models for gc was compared, and then field ET was estimated using the Penman–Monteith equation. Results indicate that the variation of gs was similar to that of PAR and the Jarvis model could better express the response of gs to PAR, vapour pressure deficit and air temperature. Compared to the W model, WI model could effectively improve the estimation accuracy of gc, with the relative error of 4.4%. Penman–Monteith equation overestimated λET by 9.4% using the estimated gc by the W model, but underestimated λET by 2.3% using the estimated gc by the WI model. Therefore, Penman–Monteith equation can estimate maize field ET using the estimated gc by WI model in the region.

► A weighted integration model (WI model) was established on the basis of weighted model (W model). ► Nonlinear relationship between leaf stomatal conductance (gs) and PAR was considered. ► WI model can effectively improve the estimation accuracy of canopy conductance (gc) from gs. ► Penman-Monteith equation underestimated λET by 2.3% using the estimated gc by the WI model.

Related Topics
Physical Sciences and Engineering Earth and Planetary Sciences Atmospheric Science
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