Simulation of Canopy Conductance of Qinghai Spruce ( Picea crassifolia) Plantation based on Granier’s Thermal Dissipation Probe Method

【Objective】Environmental factors are the main factors influencing canopy water use. In this study,Qinghai spruce,a main tree species in Loess Plateau,was used as the research object,and the evapotranspiration characteristics were analyzed,in order to investigate the adaptability of different canopy conductance( g_c ) models. 【Method】In June 2013,the evapotranspiration of Qinghai spruce was monitored with Granier’s thermal dissipation probe by a time step of 15 min. The quarter-hourly g_c was continuously simulated by the inversed Penman-Monteith model using the collected data by Granier’s thermal dissipation probes. Accounting for the lag time,a multivariate linear model and six Jarvis models were used to simulate the relationships between g_c and three key meteorological parameters of saturated vapor pressure deficit( D),air temperature( T) and solar radiation( R). A cross-validation method was employed,that is,the data collected on odd days were used to calculate g_c ,and the calculated results were verified by the data collected on even days. 【Result】In the studied Qinghai spruce forest,canopy transpiration lagged meteorological factors by 15 minutes.Canopy transpiration( E_c ) was a quadratic function of R( P < 0. 000 1),and g_c was an exponentially decreasing function of D and T( P < 0. 000 1). Although multivariate linear methods yielded slightly lower regression coefficients of g_c estimation( r~2= 0. 9) than Jarvis methods( 0. 91 ≤ r~2≤ 0. 92),they provided the best daily E_c estimation from the predicted g_c . Furthermore,all of the predicted g_c /E_c values were consistent with the measured g_c /E_c ,indicating thatall methods could predict g_c with sufficiently high accuracy.【Conclusion】R was the main driving force of E_c of the Qinghai spruce canopy. The 7 models all have high accuracy,but the Jarvis model has many patterns and complex applications.The undetermined coefficients of the some models can have infinite solutions which are quite different. However,the multivariate linear model is simple in form and high in precision,which is a better choice for simulating g_c.