Effect of topography on simulated net primary productivity spatial scaling in a mountainous landscape

摘要

Gridding the land surface into coarse homogeneous pixels may cause important biases on ecosystem model estimations of carbon budget components at local, regional and global scales. One of the main causes resulted in these biases is overlooking of sub-pixel variability of topography, especially in a mountainous area. This study analyzes the significance of topography to correct net primary productivity (NPP) estimates, made at coarse spatial resolutions where the land surface is considered as homogeneous within each pixel. Its application to a remote sensing process-based model estimates made at a 1-km resolution over a mountainous forested watershed located in Baohe River Basin in China. Results of this study show that NPP spatial scaling in complex terrain depends on the amount of the distortion of the soil moisture field at the coarse resolution, and the spatial redistribution and movement of soil water in complex terrain tightly affect NPP distribution, suggest that it is indeed necessary to consider topography in NPP spatial scaling.