Welcome to visit Scientia Silvae Sinicae，Today is

Scientia Silvae Sinicae ›› 2018, Vol. 54 ›› Issue (3): 8-18.doi: 10.11707/j.1001-7488.20180302

Previous Articles     Next Articles

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

Hu Xingbo1,2, Lu Xinjian1, Yu Yang3, He Kangning1   

  1. 1. School of Water and Soil Conservation, Beijing Forestry University Beijing 100083;
    2. Beijing Shoufa Tianren Ecological Landscape Co., Ltd. Beijing 102600;
    3. Department of Sediments Research, China Institute of Water Resource and Hydropower Research Beijing 100048
  • Received:2017-02-08 Revised:2018-01-31 Online:2018-03-25 Published:2018-04-13

PDF (PC)

347

Abstract: [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 (gc) 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 gc 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 gc 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 gc, 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 (Ec) was a quadratic function of R(P<0.000 1), and gc was an exponentially decreasing function of D and T (P<0.000 1). Although multivariate linear methods yielded slightly lower regression coefficients of gc estimation (r2=0.9) than Jarvis methods (0.91 ≤ r2 ≤ 0.92), they provided the best daily Ec estimation from the predicted gc. Furthermore, all of the predicted gc/Ec values were consistent with the measured gc/Ec, indicating that all methods could predict gc with sufficiently high accuracy.[Conclusion] R was the main driving force of Ec 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 gc.

Key words: transpiration, Qinghai spruce(Picea crassifolia), Jarvis model, canopy conductance, sap flow, TDP(thermal dissipation probe)

CLC Number: