Evaluation of the effect of selective logging on the energy-water and carbon exchange processes

This paper discusses the effect of selective logging on the energy, water, and carbon exchange of tropical forest. We apply multi-objective sensitivity analysis and parameter estimation procedures (MOGSA-UA and MOSCEM-UA) developed at the University of Arizona, USA, to the Simple Biosphere Model 2 (SiB2) at a single site in the Amazon Basin (specifically, the Santarem km 83 - LBA site) under two different conditions, i.e. before and after selective logging of the natural forest. It is assumed that logging did not change soil parameters and the results confirm our working hypothesis that the limited changes in the vegetation cover also do not greatly affect the preferred model parameter values in these two cases. However, the results do show that parameter identification procedures are able to retrieve meaningful values for the parameters and do yield an improvement of between 30 and 70% in the root mean square error when compared to using the default parameter values in SiB2.

[1]  S. Sorooshian,et al.  Effective and efficient global optimization for conceptual rainfall‐runoff models , 1992 .

[2]  Scott D. Miller,et al.  BIOMETRIC AND MICROMETEOROLOGICAL MEASUREMENTS OF TROPICAL FOREST CARBON BALANCE , 2004 .

[3]  Scott D. Miller,et al.  SEASONALITY OF WATER AND HEAT FLUXES OVER A TROPICAL FOREST IN EASTERN AMAZONIA , 2004 .

[4]  E. Davidson,et al.  The role of deep roots in the hydrological and carbon cycles of Amazonian forests and pastures , 1994, Nature.

[5]  W. J. Shuttleworth,et al.  Parameter estimation of a land surface scheme using multicriteria methods , 1999 .

[6]  Piers J. Sellers,et al.  Amazonian Deforestation and Regional Climate Change , 1991 .

[7]  A. Dalcher,et al.  A Simple Biosphere Model (SIB) for Use within General Circulation Models , 1986 .

[8]  Soroosh Sorooshian,et al.  Multi-objective global optimization for hydrologic models , 1998 .

[9]  C. Justice,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part II: The Generation of Global Fields of Terrestrial Biophysical Parameters from Satellite Data , 1996 .

[10]  D. Mocko,et al.  Simulation of high latitude hydrological processes in the Torne-Kalix basin : PILPS phase 2(e) - 2: Comparison of model results with observations , 2003 .

[11]  W. James Shuttleworth,et al.  Eddy correlation measurements of energy partition for Amazonian forest , 1984 .

[12]  W. J. Shuttleworth,et al.  Evaporation from Amazonian rainforest , 1988, Proceedings of the Royal Society of London. Series B. Biological Sciences.

[13]  H. V. Guptaf,et al.  Using a multiobjective approach to retrieve information on surface properties used in a SVAT model , 2004 .

[14]  W. James Shuttleworth,et al.  Calibrating the Simple Biosphere Model for Amazonian Tropical Forest Using Field and Remote Sensing Data. Part I: Average Calibration with Field Data , 1989 .

[15]  D. Randall,et al.  A Revised Land Surface Parameterization (SiB2) for Atmospheric GCMS. Part I: Model Formulation , 1996 .

[16]  Soroosh Sorooshian,et al.  Sensitivity analysis of a land surface scheme using multicriteria methods , 1999 .

[17]  Zong-Liang Yang,et al.  Comparative Evaluation of BATS2, BATS, and SiB2 with Amazon Data , 2000 .

[18]  S. Sorooshian,et al.  Effective and efficient algorithm for multiobjective optimization of hydrologic models , 2003 .