Modelling surface conductance of pine forest

• Published in: Agricultural and forest meteorology Vol. 43; no. 1; pp. 19 - 35
• Main Author: Stewart, J.B
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.06.1988; Oxford Elsevier; New York, NY
• Subjects: Agricultural and forest climatology and meteorology. Irrigation. Drainage; Agricultural and forest meteorology; Agronomy. Soil science and plant productions; Animal and plant ecology; Animal, plant and microbial ecology; Autoecology; Biological and medical sciences; Biometrics, statistics, experimental designs, modeling, agricultural computer applications; Fundamental and applied biological sciences. Psychology; General agronomy. Plant production; Generalities. Biometrics, experimentation. Remote sensing; Plants and fungi; Water balance and requirements. Evapotranspiration; Conductance(fluid); Water; Pinus nigra; Forests; Europe; United Kingdom; Great britain; Pinus; Pinus sylvestris; Statistical method; Transpiration; Bioclimatology; Gymnospermae; Softwood forest tree; Evapotranspiration; Parameter; Coniferales; Spermatophyta
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/0168-1923(88)90003-2

To investigate methods of estimating the surface conductance for use in the Penman-Monteith equation, four models were evaluated. In the simplest model the surface conductance was independent of all environmental variables, whereas in the most complex model the surface conductance was a non-linear function of solar radiation, specific humidity deficit, temperature and soil moisture deficit. The 584 hours of energy budget Bowen ratio measurements of evaporation made over Thetford Forest, which were used to derive the hourly values of the surface conductance of the forest under dry canopy conditions, were split into two independent sets by taking alternate days. One set was used to determine the parameters in the four models using multivariate optimisation, while the other set was used to assess the accuracy of the estimates of surface conductance and transpiration. As the complexity of the models increased, the difference in the total transpiration decreased from 22% to less than 1%. Also, bias at low and high values of the measured surface conductance decreased. However, investigation of the success of the models for estimating the surface conductance in different years showed the results were much poorer. The parameters in the most complex model were determined using the 1976 data and the 1974 and 1975 data sets used to evaluate the accuracy of the estimates. The difference in the total transpiration was 14 and 11 per cent for the two years. Also the estimated surface conductance was too large at low values of the measured surface conductance and too small at high values.